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Data Mining is one of the greatest critical aspects of automatic disease diagnosis and disease prediction. It includes data mining algorithms and techniques to study medicinal data. Recently, liver disorders have frequently increased and liver illnesses have become one of the greatest deadly diseases in different countries. In this paper, we collected 534 instances of Iraqi liver patients from Baqubah Teaching Hospital. This collected dataset includes several elements such as Age, Total Bilirubin, Direct Bilirubin, Gender, Aspartate Aminotransferase, Total Proteins, and Albumin and Globulin ratio. This paper explores the early prediction of liver disease using various data mining algorithms. The main aim of this paper is to compute the performance of many data mining techniques and compare their performance with the performance of The Indian Liver Patient Dataset. We applied three classification algorithms and parameters like accuracy, precision, recall, and f-measure were investigated to evaluate the performance of these classifiers. [ABSTRACT FROM AUTHOR]

Medical information retrieval demands terminology understanding which indicates the needs for domain specific knowledge. This paper presents a medical retrieval model called IntelligentMedicalSearch system (IMS). The contribution of the paper is four-fold: (i) medical-aware query expansion technique; (ii) MeSH-manipulated indexer which entails medical terminologies and their synonym (iii) extended Boolean matching to measure similarity between query and documents; (iv) comprehensive ranking method which prioritizes matched expanded query size besides sole total occurrence score. Result shown that (i) enrichment of query expansion using synonym term can improve mean average precision (MAP) value as opposed to standard query expansion; (iii) our comprehensive ranking method achieved high recall and according to MAP score we are in the top four run system amongst submitted run systems in ImageCLEF2010 medical task. [ABSTRACT FROM PUBLISHER]

To get the liver image segmentation from the whole abdominal medical image lays the foundation of liver three-dimensional reconstruction system, in that a good image segmentation result really makes a big difference in the three-dimensional reconstruction. This paper focuses on the research into Graph Cuts image segmentation algorithm, especially its energy function. Improved Gaussian distribution which represents the similarity probability of the gray values between adjacent nodes is selected as the energy function in this paper to do the realization of the liver image segmentation. Then the Ray Casting algorithm was adopted to achieve the three-dimensional reconstruction image of liver. Experiments show that good results have been achieved in the segmentation and three-dimensional reconstruction for liver image. [ABSTRACT FROM PUBLISHER]

Object recognition is usually processed based on region segmentation algorithm. Region segmentation in the IT field is carried out by computerized processing of various input information such as brightness, shape, and pattern analysis. If the information mentioned does not make sense, however, many limitations could occur with region segmentation during computer processing. Therefore, this paper suggests effective region segmentation method based on R2 information within the magnetic resonance (MR) theory. In this study, the experiment had been conducted using images including the liver region and by setting up feature points of R2 map as seed points for region growing to enable region segmentation even when the border line was not clear. As a result, an average area difference of 8.5%, which was higher than the accuracy of conventional region segmentation algorithm, was obtained. [ABSTRACT FROM PUBLISHER]

In this paper the goal was to measure the contrast to noise ratio (CNR) of fast spin echo (FSE) magnetic resonance imaging (MRI) sequences in detecting thermal lesions created by high intensity focused ultrasound (HIFU) in rabbit kidney, liver, heart, and brain and lamb pancreas. A spherically focused transducer was used which is navigated inside MRI by a custom made positioning device. A simple simulation model was developed which predicts the CNR for the two FSE MRI sequences. The maximum contrast measured with T1-W FSE ranges from 10 to 25. For all 5 tissues of interest if one uses TR between 400 and 500 ms the contrast is maximized. The T1, and T2 value of lesion depends strongly on the host tissue and is always lower than the host tissue. The greater the difference in T1 value, the greater the CNR. The simulated model for predicting the CNR was proven successful. The CNR measured with T2-W FSE varies between 12 and 15 for all 5 tissues. With T2-W FSE if one uses TE between 40 and 50 ms, the contrast is maximized. [ABSTRACT FROM AUTHOR]

The lobule is the structural unit of the liver. In this paper a multi-physical model of blood flow in the liver lobule is considered. The proposed model is built on the basis of a double porosity model for the process of blood flow which is coupled with linear elasticity for deformations. The computational algorithm is based on finite-element approximation in space and explicit-implicit approximation in time which is a splitting scheme by physical processes. Results of numerical experiments are demonstrated. [ABSTRACT FROM AUTHOR]

Manual segmentation of liver computerized tomography (CT) images is very time consuming, so it is desired to develop a computer-based approach for the analysis of liver CT images that can precisely segment the liver without any human intervention. This paper presents normalized cuts graph partitioning approach for liver segmentation from CT images. To evaluate the performance of the presented approach, we present tests on different liver CT images. Experimental results obtained show that the overall accuracy offered by the employed normalized cuts technique is high compared to the well known K-means segmentation approach. [ABSTRACT FROM PUBLISHER]

Image segmentation is an essential process for most analysis tasks of medical images. That's because having good segmentation results is useful for both physicians and patients via providing important information for surgical planning and early disease detection. This paper aims at evaluating the performance of the K-means clustering algorithm. To achieve this, we applied the K-means approach on different medical images including liver CT and breast MRI images. Experimental results obtained show that the overall segmentation accuracy offered by the K-means approach is high compared to segmentation accuracy by the well-known normalized cuts segmentation approach. [ABSTRACT FROM PUBLISHER]

Due to intensity overlapping, blurred edges and complex backgrounds with clutter features, liver segmentation is still a challenging task. In this paper, we address it with a constrained convex variational model, which can definitely avoid leakage through anatomical knowledge from users. A novel heuristic intensity model is proposed to suppress irrelevant strong edges and constrain the segmentation. Both global and local region appearance information are integrated to model higher level features such as local context. As a result, weak liver boundaries and fine structures can be stably delineated according to the information from neighborhood and nearby layers. No precise prior segmentation is needed and few seeds without shape restriction, about three seeds, are adequate to capture fine structures. The initialization is also very easy. Moreover, an accelerated primal-dual algorithm is proposed to efficiently and globally optimize the model. Our method is validated on MICCAI dataset and produces a high score of 80.6. It can be used to segment other abdominal organs. [ABSTRACT FROM PUBLISHER]

This paper reports a difference proportional cell contact platform for three dimension hepatocyte culture. We designed the cell wires about the width of 25 micrometer by dielectrophoresis for difference contact area. The platform was consisted of two dimensional cell contact chambers and three dimensional liver tissue chambers by dielectrophoresis pattern method and microfluidic channel design. For cell contact chambers, we used dielectrophoresis pattern method to make difference contact area for difference proportional cell communication. For liver tissue chambers, we used the UV-initiated solution of the poly (ethylene glycol)-diacrylate (PEG-DA) had been exposed to form microwells to pattern three dimension lobule-mimetic structure liver tissue in vitro. HepG2 cells were loading with three dimensional PEG-DA-dased micro-structures for artificial lobule pattern. Finally, we showed liver functional albumin testing. The albumin secretion of liver pattern chambers with HMEC-1 and C2C12 co-culture communication was 34% higher than the albumin secretion of liver chip without cells communication. [ABSTRACT FROM PUBLISHER]

In this paper, we present a system for segmenting the 3D liver region from CT images and reconstructing its 3D model. The segmentation is accomplished in 3-D space which is extended from the user controlled 2-D random walker technique and implemented by a slice-section method. After obtaining the 3D liver segmentation result, we apply the surface reconstruction algorithm based on bipartite polar classification to build the 3-D liver surface model. In the experimental results, we apply the proposed algorithm to ten test CT datasets to evaluate its accuracy and we demonstrate the good accuracy compared with the human labeled results. [ABSTRACT FROM PUBLISHER]

The study found the mucus secreted by fish skin mucus cells, it can defense predators, microorganisms and parasites' invade and attack. This paper wants to discuss extracts of fresh eel mucus physiological effect on Anguilla japonica. The method of tube feeding is used to feed rat for four weeks, and then their biochemical indicators of liver and kidney function are measured. Moreover, the method of GM(0,N) model in grey system theory is presented, and the liver and kidney function of eel mucus is used as influence factor to evaluate it's the physiological effects. Through the analyzing results, the values of biochemical indicators of liver and kidney function of rat body weight can be achieved, and the results are quite matching with the previous research in soft computer area. Hence, it not only can help researchers understand biochemical effects on rat, but also can provide references for future research. [ABSTRACT FROM PUBLISHER]

Automatic lesion detection is important for cancer examination and treatment, whereas it remains challenging due to the varied shape, size, and contextual anatomy of the diseased masses. In this paper, we present a robust and effective learning based method for automatic detection of liver lesions from computed tomography data. The contributions of this paper are the following. First, we develop a cascade learning approach to lesion detection comprising multiple detectors in the spirit of marginal space learning. Second, a gradient based locally adaptive segmentation method is proposed for solid liver lesions. The segmentation results are used to extract informative features for classification of generated candidates. Extensive experimental validation is carried out on 660 volumes with 1,302 hypodense lesions, and 234 volumes with 328 hyperdense lesions, with a resulting 90% detection rate at 1.01 false positives per volume for hypodense lesion and 1.58 false positives per volume for hyperdense lesion, respectively. [ABSTRACT FROM PUBLISHER]

Mass Spring Model (MSM) is a highly efficient model in terms of calculations and easy implementation. Mass, spring stiffness coefficient and damping constant are three major components of MSM. This paper focuses on identifying the coefficients of spring stiffness and damping constant using automated tuning method by optimization in generating human liver model capable of responding quickly. To achieve the objective two heuristic approaches are used, namely Simulated Annealing (SA) and Genetic Algorithm (GA) on the human liver model data set. The properties of the mechanical heart, which are taken into consideration, are anisotropy and viscoelasticity. Optimization results from SA and GA are then implemented into the MSM to model two human hearts, each with its SA or GA construction parameters. These techniques are implemented while making FEM construction parameters as benchmark. Step size response of both models are obtained after MSMs were solved using Fourth Order Runge-Kutta (RK4) to compare the elasticity response of both models. Remodelled time using manual calculation methods was compared against heuristic optimization methods of SA and GA in showing that model with automatic construction is more realistic in terms of realtime interaction response time. Liver models generated using SA and GA optimization techniques are compared with liver model from manual calculation. It shows that the reconstruction time required for 1000 repetitions of SA and GA is faster than the manual method. Meanwhile comparison between construction time of SA and GA model indicates that model SA is faster than GA with varying rates of time 0.110635 seconds/1000 repetitions. Real-time interaction of mechanical properties is dependent on rate of time and speed of remodelling process. Thus, the SA and GA have proven to be suitable in enhancing realism of simulated real-time interaction in liver remodelling. [ABSTRACT FROM AUTHOR]

This paper mainly studied the use of computer-aided techniques to calculate the volume of liver tumor. CT images of liver tumor were firstly processed by the optimized non-sampling Contourlet Transform method proposed in this paper for image enhancement. The enhanced CT images of liver tumors were then segmented by the Chan-Vese model. Finally, the cumulative sum method was used to compute the volume of liver tumor. The experimental result shows the method of liver tumor computation used in this paper achieve lower error rate than the manual computation method and the VTK method. [ABSTRACT FROM PUBLISHER]

Traditional Chinese Medicine (TCM) has been widely used to treat various diseases like infectious diseases. Treatment Based on Syndrome Differentiation (TBSD) is the main principle in TCM clinical practice. So exploring the relationships between diagnoses and treatments from successful cases is important and valuable for better treating hepatitis diseases, which is a decision support problem based on data warehouse in nature. In this paper, using the multidimensional analysis techniques of BusinessObjects (BO) platform, we introduce a series of online analytical processing (OLAP) reports which cover different subjects of TCM on hepatitis diseases and a corresponding system used to manage the reports. It has been found that these OLAP reports are useful in experience sharing of making diagnoses and giving treatments on hepatitis diseases. [ABSTRACT FROM PUBLISHER]

Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Accurate computation of one pixel wide medial surfaces is mandatory. Those surfaces must represent faithfully the geometry of the volume. Although morphological methods produce excellent results in 2D, their complexity and quality drops across dimensions, due to a more complex description of pixel neighborhoods. This paper introduces a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Our experiments show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume. [ABSTRACT FROM PUBLISHER]

In this paper, we present a novel approach to rigidly register intraoperative electromagnetically tracked ultrasound (US) with pre-operative contrast-enhanced magnetic resonance (MR) images. The clinical rationale for this work is to allow accurate needle placement during thermal ablations of liver metastases using multimodal imaging. We adopt a model-based approach that rigidly matches segmented liver surface shapes obtained from the multimodal image volumes. Towards this end, a shape-constrained deformable surface model combining the strengths of both deformable and active shape models is used to segment the liver surface from the MR scan. It incorporates a priori shape information while external forces guide the deformation and adapts the model to a target structure. The liver boundary is extracted from US by merging a dynamic region-growing method with a graph-based segmentation framework anchored on adaptive priors of neighboring surface points. Registration is performed with a weighted ICP algorithm with a physiological penalizing term. The MR segmentation model was trained with 30 datasets and validated on a separate cohort of 10 patients with corresponding ground truth. The accuracy and robustness of the method were assessed by registering four US/MR datasets, yielding accurate landmark registration errors (3.7 ± 0.69mm) and high robustness, and is thus acceptable for radiofrequency clinical applications. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an automated liver segmentation method to overcome the challenging issue of similar intensities shared by liver and its surrounding tissues in low-contrast CT images. Our approach takes advantage of PET data to initialize the CT liver region of interest (ROI), and then applies anisotropic diffusion on the CT liver ROI to suppress the intensity values of adjacent structures and hence to highlight the liver region. The regularized 3D Chan-Vese level-set model with distance regularized term is introduced to segment the CT liver volume. Experimental results on 40 clinical PET-CT studies demonstrated that without relying on any training datasets, our method achieved accurate and robust normal liver segmentation in low-contrast CT volumes from PET-CT scanners. [ABSTRACT FROM PUBLISHER]

Recently a growing interest has been seen in minimally invasive treatments with open configuration magnetic resonance (Open-MR) scanners. Because of the lower magnetic field (0.5T) and various different surgical conditions, sometimes tumors can not be visualized clearly on Open-MR volumes. Combining of CT volumes acquired before surgery, it is possible to identify the tumor's location by application of registration techniques. In this paper, we proposed a non-rigid registration method combined with a semi-automatic liver segmentation method for MR-Guided Liver Cancer Surgery. We first propose a robust method using K-means clustering and graph cut to segment liver from low contrast open MR images and then a free-form deformation based non-rigid registration method is applied to the segmented livers. [ABSTRACT FROM PUBLISHER]

Content-based image retrieval (CBIR) is an image search technique that utilises visual features as search criteria; it has potential clinical applications in evidence-based diagnosis, physician training, and biomedical research. Graph-based CBIR techniques have high accuracy when retrieving images by the similarity of the spatial arrangement of their constituent objects but these techniques were initially designed for single-modality images and have limited retrieval capabilities when multi-modality images, such as combined positron emission tomography and computed tomography (PET-CT), are considered. In this paper, we present a graph-based CBIR approach for multi-modality images that integrates modality-specific features on graph vertices and adapts a well-established graph similarity scheme to account for varying vertex feature sets. Furthermore, we propose a graph pruning method that removes redundant edges using the spatial proximity of image regions. We evaluated our work using two simulated data sets, consisting of 2D liver shapes and 3D whole-body lymphoma images. In our experiments we achieved a higher level of retrieval precision using our graph method when compared to conventional graph-based retrieval, demonstrating that our proposed method enabled new capabilities and improved multi-modality CBIR. [ABSTRACT FROM PUBLISHER]

This paper describes a method for tracking a tumour using the planar projections of fiducial markers as surrogates. The projections can originate from various sources such as a beam-eye view X-ray, a portal imager or a fluoroscope. The two-dimensional position of the fiducial markers in the planar image in conjunction with a population-based statistical motion model is used to accurately predict and track the motion of a target volume during treatment. The basic assumption is that the projected surrogate locations contain valuable information about the in-plane motion of the lesion whereas the statistical motion model helps to describe the unobserved out-of-plane motion of the target volume. We analysed the accuracy with regard to varying the camera position and uncertainty in the measurement of the surrogate positions to simulate image noise and camera registration errors. The experiments showed that the tumour motion can be robustly predicted with an accuracy of 2.6 mm over a wide range of target volumes and treatment field directions despite a measurement error of σ = 2 mm for the fiducials. [ABSTRACT FROM PUBLISHER]

In the electromagnetic spectrum, Terahertz (THz) radiation is located between the infrared and microwave regions. As a result of recent advances in THz technology, numerous opportunities have opened up in this part of the spectrum. The THz frequency range stimulates substantial amplitude vibrational modes of molecules. Water has strong absorptions at THz frequencies and water being a major constituent of different biological specimens, THz radiation is likely to demonstrate significant characteristic distinction between them. Terahertz pulsed imaging (TPI) and terahertz pulsed spectroscopy (TPS) are non-ionizing and non-invasive analyzing technique that have recently been used to study a wide range of biological materials, and have been shown to have potential in medical and biological applications. Despite this enormous potential, little research has been conducted made on appropriate THz sources for biomedical applications. The power levels and frequencies suitable are still not well-defined. In this paper, we summarize some of the available THz sources, applied power levels of irradiation, and suitable frequency ranges that have been utilized in particular studies and discuss the findings regarding tissue identification, disease detection, and cancer diagnosis. [ABSTRACT FROM PUBLISHER]

A 256 element toroidal piezocomposite transducer with a diameter of 70 mm and a radius of curvature of 70 mm working at 3MHz was used. A 7.5 MHz ultrasound imaging probe was integrated to the centre of the HIFU transducer. This paper discusses the interest in using real-time hand held elastography to guide a HIFU treatment. 16 lesions were produced and imaged intra-operatively in vivo in 4 pigs. Strain images were obtained and displayed at a frame rate identical to that of the sonograms (23 frames/s) using the ultrasound imaging probe placed in the centre of the HIFU device. The compression was applied manually. At the end of the procedure the liver was removed and imaged using a 1.5 T MR-scanner. The dimensions of the coagulated volumes measured on gross pathology were 22.1 mm (average diameter) and 19.8 mm (average depth). The contrast between ablated and untreated liver was higher on strain images (23dB) than on the B-Mode (3dB), T1-weighted (3dB) and T2-weighted images (13dB). The correlation between dimensions measured on gross pathology and dimensions measured on B-mode images, strain images, T1-weighted and T2-weighted images were r = 0.51, r = 0.68, r = 0.72 and r = 0.74 respectively. The correlation between dimensions measured on strain images and dimensions measured on T1-weighted and T2-weighted images were r = 0.77 and r = 0.78 respectively. In conclusion, the device presented in this study allows the creation of large ablations volumes over short periods of time. In addition, these in vivo results show that realtime hand-held strain imaging performed with an ultrasound probe integrated to the HIFU device can be used intra-operatively to visualize the dimensions of HIFU ablations with a precision similar to MRI, but with improved contrast. [ABSTRACT FROM AUTHOR]

Presented in this paper is a tumor-mimic model that allows the evaluation at a preclinical stage of the targeting accuracy of HIFU treatments in the liver. The tumor-mimics were made by injecting a warm mixture of agarose, cellulose, and glycerol that polymerizes immediately in hepatic tissue and forms a 1 cm discrete lesion that is detectable by ultrasound imaging and gross pathology. Three studies were conducted: (i) in vitro experiments were conducted to study acoustical proprieties of the tumor-mimics, (ii) animal experiments were conducted in ten pigs to evaluate the tolerance of the tumor-mimics at mid-term (30 days), (iii) ultrasound-guided HIFU ablation has been performed in ten pigs with tumor-mimics to demonstrate that it is possible to treat a predetermined zone accurately. The attenuation of tumor-mimics was 0.39 dB.cm-1 at 1 MHz, the ultrasound propagation velocity was 1523 m.s-1, and the acoustic impedance was 1.8 MRayls. The pigs tolerated tumor-mimics and treatment well over the experimental period. Tumor-mimics were visible with high contrast on ultrasound images. In addition, it has been demonstrated by using the tumor-mimic as a reference target, that tissue destruction induced by HIFU and observed on gross pathology corresponded to the targeted area on the ultrasound images. The average difference between the predetermined location of the HIFU ablation and the actual coagulated area was 16%. These tumor-mimics are identifiable by ultrasound imaging, they do not modify the geometry of HIFU lesions and thus constitutes a viable mimic of tumors indicated for HIFU therapy. [ABSTRACT FROM AUTHOR]

The present study was designed to evaluate the effect of different concentrations of cold aqueous extract of wheatgrass on the histological structures of the liver in male albino rats as it was taken orally with the extract in three doses (100, 150, 200 mg / kg) (Body Weight) for 30 days, wheatgrass is rich in Vitamin C, Selenium, Phosphorous, Iron, Potassium, Sulfur, Sodium, Cobalt, Zinc, and others. In addition, wheatgrass contains phenols, flavonoids, and tocopherols, which act as antioxidants. After the experiment period ended, the animals were anesthetized, dissected and liver samples were taken, and they were fixed in formalin at a concentration of 10%. The slides were prepared and the results showed that the live tissue of mice treated with aqueous extract of wheatgrass at a concentration of (100.150.200 mg / kg / body weight) for a period of (30) days did not suffer from any change in the histological composition compared to the control group, and the study indicated that eating wheatgrass Important because they contain effective compounds that help the immune system to suppress free radicals that may be generated in the body as a result of consuming a lot of food additives. Therefore, the cold aqueous extract of wheatgrass can be considered safe to handle and does not damage body tissues. [ABSTRACT FROM AUTHOR]

The aim of this study was to measure AST, ALT, GGT, TP, LDH, and albumin in patients with breast cancer to assess ceruloplasmin, Cu, SA, and liver. Materials and Procedures: The research was completed.Materials and Methods: The research was conducted at Kirkuk Teaching Hospital. The study included 64 women who had BC. Their ages ranged from 30 to 56 years old. The control group consisted of 64 matched normal individuals. Patients had lower total protein and albumin concentrations than the control group. The findings suggest that serum sialic acid levels may be useful in the diagnosis of disese. [ABSTRACT FROM AUTHOR]

The United Network for Organ Sharing is planning to resolve the ever-growing geographic disparities in kidney transplantation. Currently available simulation techniques are limited in their ability to analyze the impact of policy changes at the system level. This paper discusses the development of a discrete event simulation of the kidney transplantation system, KSIM. KSIM design is discussed and can easily be adapted to test alternative geographic organ allocation policies. Input analysis employing actual transplantation system data was conducted to best represent patient and organ arrival processes. After discussing our model, we briefly describe how KSIM was verified and validated against twenty years of actual transplantation system information. We also describe the potential usability of KSIM in organ allocation policy development. [ABSTRACT FROM PUBLISHER]

In this paper, we proposed a new approach for image clustering to address the adverse effects of noise presented in the images. In particular, the concept of information gain has been incorporated into classical fuzzy c-means (FCM) algorithm in order to develop a robust clustering method. FCM is associated with high sensitivity to noise and produces non-homogenous clustering. To induce robustness to noise, the new clustering technique updates fuzzy membership values and cluster centroids based on information gain. The proposed method produces more homogeneous clustering and its performance can be verified at noisy and noise free images. Experiments have been performed on synthetic, CT liver images and compared with those of classical FCM and one of its robust variants. Moreover, the proposed algorithm has been validated on a data set of 30 carotid artery ultrasound images. Visual inspection of segmented images and clustering quality measures confirm that the proposed approach outperforms other clustering algorithms in comparison. Quantitative measures, in terms of PC and CE, also lead to similar conclusion. Hence, the proposed algorithm is robust to noise and produces homogenous clustering. [ABSTRACT FROM PUBLISHER]

In this paper, an approach based on generalized gradient vector flow (GGVF) snake model is proposed for automatic segmentation of liver tumor ultrasound images. According to it the initial contour of GGVF snake can be generated automatically in stead of artificial appointment. The preprocess including anisotropic diffusion filtering and texture classification is implemented on ultrasound images, which ensures the initial contour close to the tumor's real boundaries. The edge map function of GGVF is also modified for obtaining better segmenting performance on ultrasound images. Experimental results show the approach is suitable and effective for segmentation of liver tumor in ultrasound images. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an effective approach towards color image segmentation for micro-vessel detection in the virtual slide of double stained liver tissue. The contribution of the proposed method lies in three aspects. First, the dominant colors of white/gray, blue, red and brown are modeled in the RGB color space. Second, the CART (classification and regress tree) method is implemented to segment the modeled colors. Third, the micro-vessel regions are identified in the color images based on the association of both red and brown pixels. Extensive experiments are carried out to validate the performance of the proposed approach. The experimental results demonstrate that our method is quite promising. [ABSTRACT FROM PUBLISHER]

Recently, the death rate due to the liver cancer rises remarkably. To reduce the rate, the early detection of the disease is important. To detect diseases in early stage which are concern cancer, image diagnosis such as CT image is used in medical fields. On the other hand, the burden to a radiologist becomes increase. Therefore, the development of a system reducing the burden of the radiologist is important. In order to diagnose abnormalities based on medical imaging there are some reports. But, there is no report which is concern with detecting abnormality on liver disease based on temporal subtraction technique for abdominal CT image. As one of the methods to analyze abnormalities on visual screening, temporal subtraction technique is useful. This technique subtracts past image to current one. To obtain the good performance based temporal subtraction technique, image registration is most important task. In this paper, we propose a registration method for liver CT image using voxel matching techniques. We describe our registration method from two CT image which obtained deference time series and shows experimental results with discussion. [ABSTRACT FROM PUBLISHER]

Liver segmentation from computer tomography scans is a topic of research interest, as the acquisition and inter-patient variability make the automatic segmentation difficult. The current trend is to improve the accuracy and to reduce the computational complexity of the segmentation, as this is essential for the diagnostic and for 3D rendering. We propose a new computationally efficient approach for 3D liver segmentation, based on the 3D Discrete Cosine Transform applied on volume blocks for feature extraction, followed by a support vector machine classification of volume blocks. The segmentation is refined in a post-processing step through a 3D median filtering, 3D morphological operations, and 3D connected components analysis. This new method has been applied on real liver volumes and provided promising results, on the level of the state of the art, with a significant reduction in the data to be processed and in the operations involved as compared to other approaches. [ABSTRACT FROM PUBLISHER]

This paper presents an approach for understanding the soft tissue behavior in surface contact with a hard object scanning the tissue. The application domain is confocal microlaparoscope imaging, mostly used for imaging the outer surface of the organs in the abdominal cavity. The probe (optic-head) is swept over the tissue to collect sequential images to obtain a large field of view with mosaicing. The problem we address is that the tissue also moves with the probe due to its softness; therefore the resulting mosaic is not in the same shape and dimension as traversed by the probe. Our approach inspires from the finger slip studies and adapts the idea of load-and-slip that explains the movement of the finger when dragged on a hard surface. We propose the concept of loading-distance and perform measurements with in total 84 experiments on beef liver and chicken breast tissues. Our results indicate that the loading-distance can be measured prior to a scan and be used during the scan in order to compensate the movement of the probe. In this way we can have an image-mosaic of the tissue surface in a desired shape. [ABSTRACT FROM PUBLISHER]

Probe-based confocal laser endomicroscopy is a recent tissue imaging technology that requires placing a probe in contact with the tissue to be imaged and provides real time images with a microscopic resolution. Additionally, generating adequate probe movements to sweep the tissue surface can be used to reconstruct a wide mosaic of the scanned region while increasing the resolution which is appropriate for anatomico-pathological cancer diagnosis. However, properly controlling the motion along the scanning trajectory is a major problem. Indeed, the tissue exhibits deformations under friction forces exerted by the probe leading to deformed mosaics. In this paper we propose a visual servoing approach for controlling the probe movements relative to the tissue while rejecting the tissue deformation disturbance. The probe displacement with respect to the tissue is firstly estimated using the confocal images and an image registration real-time algorithm. Secondly, from this real-time image-based position measurement, the probe motion is controlled thanks to a simple proportional-integral compensator and a feedforward term. Ex vivo experiments using a Stäubli TX40 robot and a Mauna Kea Technologies Cellvizio imaging device demonstrate the effectiveness of the approach on liver and muscle tissue. [ABSTRACT FROM PUBLISHER]

This paper proposes an organ boundary determination method for detecting internal bleeding. Focused assessment with sonography for trauma (FAST) is important for patients who are sent into shock by internal bleeding. However, the FAST has a low sensitivity, approximately 42.7 %, and delays of lifesaving treatment due to internal bleeding being missed have become a serious problem in emergency medical care. This study aims, therefore, to construct an automatic internal bleeding detection robotic system on the basis of ultrasound (US) image processing to improve the sensitivity. Internal bleeding has two key features: it is extracted from low-brightness areas in US images and accumulates between organs. We developed method for extracting low-brightness areas and determining algorithms of organ boundaries by low-brightness set analysis, and we detect internal bleeding by combining these two methods. Experimental results based on clinical US images of internal bleeding between Liver and Kidney showed that proposed algorithms had a sensitivity of 77.8% and specificity of 95.7%. [ABSTRACT FROM PUBLISHER]

Segmentation of liver from volumetric images forms the basis for surgical planning required for living donor transplantations and tumor resections surgeries. This paper introduces a novel idea of using sparse representations of liver shapes in a learned structured dictionary to produce an accurate preliminary segmentation, which is further evolved using a joint image and shape based level-set framework to obtain the final segmented volume. Structured dictionary for liver shapes can be learned from an available training dataset. The proposed approach requires only 3 orthogonal segmented masks as user-input, which is less than half the number required by current state-of-the-art interaction-based methods. The increased accuracy of the preliminary segmentation translates into faster convergence of the evolution step and highly accurate final segmentations with mean average symmetric surface distances (ASSD) [1] of (1.03±0.3)mm when tested on a challenging dataset containing 62 volumes. Our approach segments a volume on an average of 5 mins and, is 25% (approx.) faster than comparably performing techniques. [ABSTRACT FROM PUBLISHER]

PET/CT attenuation correction factors are derived from the CT image. Difficulties arise in respiratory-gated PET because the attenuation map often needs to be deformed to correct for the non-rigid motion between each gated PET frame. Deformable image registration can be useful for measuring non-rigid motion, however there are some challenges which impact on its accuracy. In this paper we address these issues in noisy gated PET data. We describe an image registration algorithm that satisfies additional constraints arising from the physics of the problem. We represent the lung by a simple mechanical analogue in which a piston drives the lung tissue. Given this model, respiratory motion approximately satisfies a one-dimensional wave equation in the superior-inferior direction. An existing free-form deformation algorithm is modified to impose this constraint. The proposed algorithm for image registration is found to be extremely robust to image noise. Simulations suggest that applying the wave equation constraint is accurate. The resulting images are plausible and the constraints enhance the robustness of the algorithm when applied to clinical respiratory-gated PET. [ABSTRACT FROM PUBLISHER]

In noninvasive HIFU (High Intensity Focused Ultrasound) surgery, a treatment time can be reduced by using a therapeutic transducer capable of enlarging a coagulated lesion per sonication. Currently, most of studies have been focused on the expansion of necrosis in the lateral direction than the axial direction. In this paper, we present a novel HIFU transducer with a dual curved aperture which can extend DOF (Depth of Focus) resulting in a broad necrotic region in the axial direction. A prototype dual-curved transducer was fabricated and its performance was successfully tested by conducting simulation of bioheat transfer/thermal dose, hydrophone measurement, and in vitro test with a beef liver. Although several design parameters for the transducer were not optimized, the DOF of the proposed method was 3.5 times larger than that of the conventional single element transducer with the same dimension. Thus, the dual-curved therapeutic transducer may be a potential method to reduce treatment time of HIFU surgery. [ABSTRACT FROM PUBLISHER]

The study on the liver deformation during the needle inserted into the target lesion, plays an important role in the robot-assisted liver tumor coagulation therapy system, which impacts the operation simulation, the pre-operative surgical planning, the treatment accuracy, and the success rate. To this end, this paper presents a quasi-static finite element method to analyze the deformation of the soft tissue. According to the force modeling of the needle-insertion, the liver deformation can be divided into two states: the pre-penetration state and post — penetration state. First, both the realistic three-dimensional geometric model and the linear elastic physical model of the liver are established; second, the consecutive dynamic deformation of the liver is decomposed into several discrete quasi-static procedures, followed by the numerical simulation. The simulation results demonstrate the effectiveness and the feasibility of the proposed method. [ABSTRACT FROM PUBLISHER]

In order to solve the problems that how to mine and express classification knowledge and rules in compatibility of prescription, this paper introduces a new theory of formal concept analysis (FCA), and realizes the compatibility of prescription knowledge mining. Meanwhile, the prescription drugs of reverting yin disease treatment in Treatise on febrile diseases are selected to apply the FCA theory to mine the compatibility of prescription. The result shows that complete knowledge which is related to prescription can be obtained from the attribute partial order chart, therefore it has been proved that the theory of FCA provides a new method to discovery the new knowledge of prescription of TCP. [ABSTRACT FROM PUBLISHER]

Support vector machine is a widely used tool in the field of image processing and pattern recognition. The parameters selection plays a significant role in support vector machine(SVM). This paper proposed an improved parameter optimization method based on traditional PSO optimizing algorithm by changing the fitness function in the traditional process. And this method has achieved better results which reflected in the ROC curves in medical images classification. [ABSTRACT FROM PUBLISHER]

Mutual information is a widely-used metric in medical image registration, which achieves many good results; however, it may lead to misregistration because of the absence of spatial information. In order to solve this problem, this paper proposes an improved hybrid metric combining mutual information and spatial information. The spatial information is obtained through calculating Hausdorff fraction. In experiments, mutual information is used as a comparative method. Experiments show that the proposed method performs well in multiphase contrast-enhanced abdomen CT image non-rigid registration problems. [ABSTRACT FROM PUBLISHER]

In medical imaging research, the three-dimensional (3-D) shape representation and analysis of anatomic structures using only a few parameters is an important issues, and can be applied to computer assisted diagnosis, surgical simulations, visualization, and many other medical applications. This paper proposes the representation of the shape surfaces of a simply connected 3-D object using spherical harmonic (spharm) functions, which can provide an approximate global description of the shape using only a few spharm parameters. Spharms are obtained from several partial differential equations used in physics, such as the Laplace, Helmholtz, and Schrodinger equations, in which spherical coordinates are used. In this study, we aim to develop a 3D representation of human anatomy, such as the liver and spleen, with fewer parameters by using spharm functions. Furthermore, the experimental results show that the shape of the liver and spleen can be accurately represented with only a few spharm parameters. [ABSTRACT FROM PUBLISHER]

Abstract Objectives This article examines the impacts of race/ethnicity and nativity on differential liver cancer mortality of non-Hispanic white and Mexican-origin populations. Particular attention is given to the ways that liver cancer mortality among the Spanish-surnamed population of Texas challenges the tenets of the Epidemiologic Paradox. Methods Pooled death certificate data allow the construction of logistic regression models which test the hypothesis that the odds of liver cancer mortality among Mexican immigrants and Mexican Americans are similar to those experienced by non-Hispanic whites. Results Logit estimates reveal positive, statistically significant effects of Spanish surname and immigrant status on liver cancer mortality. Conclusions These findings offer no support for the assertion that Mexican-origin race/ethnicity and immigrant status may be protective against liver cancer mortality. [ABSTRACT FROM AUTHOR]

In nonlinear US propagation, the B/A parameter allow to quantify the nonlinear distortion of the US pulse and the apparition of the different harmonics. Previous studies highlighted the interest of the nonlinear parameter in tissue characterization or parametric imaging. In this paper, an extended comparative method (ECM) is used to image the nonlinear parameter of in vitro porcine liver. The nonlinear parameter is imaged before and after a high intensity focused ultrasound (HIFU) treatment. The resulting maps highlight the region of the lesion and show the potential of B/A imaging in HIFU applications. [ABSTRACT FROM PUBLISHER]

In this study, B ultrasound images of 124 benign and malignant patients were randomly selected as the study objects. The B ultrasound images of the liver were treated by enhanced de-noising. By constructing the gray level cooccurrence matrix which reflects the information of each angle, Principal Component Analysis of 22 texture features were extracted and combined with LM neural network for diagnosis and classification. Experimental results show that this method is a rapid and effective diagnostic method for liver imaging, which provides a quantitative basis for clinical diagnosis of liver diseases. [ABSTRACT FROM AUTHOR]

The use of glucocorticoids induces a specific pathology in dogs called steroid hepatopathy. The objective of this study was to determine the possibility of the hepatoprotectants to decrease the corticosteroid-induced alteration in dogs' liver functional condition. To reach the aim such blood serum enzymes as alaninaminotransferase (ALAT), gammaglutamyltranferase (GGT), alkaline phosphatase (AP) and corticosteroid-induced thermostable alkaline phosphatase (cAP) were analysed. The study took place in private veterinary clinics in Latvia, during 2013 - 2014, with the permission of dogs' owners. Twenty animals, which received glucocorticoids due to present diagnosis, were divided into two groups. In the first group longlasting glucocorticoid methylprednisolone acetate injection was used once, while in the second group, the hepatoprotectants were used after the injection of glucocorticoids. It was discovered that after 45 days of hepatoprotectants use, blood enzymes were significantly lower (p<0.05) than in dogs that did not receive hepatoprotectants. In the group where the hepatoprotectants were used the enzyme values reached the reference limits. [ABSTRACT FROM AUTHOR]