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To meet the requirements of navigation devices in terms of weight, power consumption, and size, it is necessary to capture low-resolution images or transmit low-resolution images to a server for object detection. However, due to the lack of details and frequency information, even state-of-the-art detection methods face challenges in accurately identifying objects. To tackle this issue, we introduce a novel upsampling method termed multi-wave representation upsampling, accompanied by a training strategy aimed at reinstating high-frequency details and augmenting the precision of object detection. Finally, we conduct empirical experiments showing that compared to alternative methodologies, our proposed approach yields images exhibiting minimal disparities in frequency compared to high-resolution counterparts. Additionally, it exhibits superior performance across objects of varying scales, while simultaneously demonstrating reduced parameter count and enhanced computational efficiency.

Cervical cancer remains a significant health concern worldwide, where precise segmentation of cervical lesions is integral for effective diagnosis and treatment planning. This systematic review critically evaluates the application of graph-based methodologies for cervical cancer segmentation, identifying their potential, drawbacks, and avenues for future development. An exhaustive literature search across Scopus and PubMed databases resulted in 20 pertinent studies. These studies were assessed focusing on their implementation of graph-based techniques for cervical cancer segmentation, the utilized datasets, evaluation metrics, and reported precision levels. The review highlights the progressive strides made in the field, especially regarding the segmentation of intricate, non-convex regions and facilitating the detection and grading of cervical cancer using graph-based methodologies. Nonetheless, several constraints were evident, including a dearth of comparative performance analysis, reliance on high-resolution images, difficulties in specific boundary delineation, and the imperative for additional validation and diversified datasets. The review suggests future work to integrate advanced deep learning strategies for heightened accuracy, formulate hybrid methodologies to counteract existing limitations, and explore multi-modal fusion to boost segmentation precision. Emphasizing the explainability and interpretability of outcomes also stands paramount. Lastly, addressing critical challenges such as scarcity of annotated data, the need for real-time and interactive segmentation, and the segmentation of multiple objects or regions of interest remains a crucial frontier for future endeavors.

With the increasing throughput of modern sequencing instruments, the cost of storing and transmitting sequencing data has also increased dramatically. Although many tools have been developed to compress sequencing data, there is still a need to develop a compressor with a higher compression ratio. We present a two-step framework for compressing sequencing data in this paper. The first step is to repack original data into a binary stream, while the second step is to compress the stream with a LZMA encoder. We develop a new strategy to encode the original file into a LZMA highly compressed stream. In addition an FPGA-accelerated of LZMA was implemented to speedup the second step. As a demonstration, we present repaq as a lossless non-reference compressor of FASTQ format files. We introduced a multifile redundancy elimination method, which is very useful for compressing paired-end sequencing data. According to our test results, the compression ratio of repaq is much higher than other FASTQ compressors. For some deep sequencing data, the compression ratio of repaq can be higher than 25, almost four times of Gzip. The framework presented in this paper can also be applied to develop new tools for compressing other sequencing data. The open-source code of repaq is available at: https://github.com/OpenGene/repaq.

Abstract Background Conventional dynamic contrast enhanced (DCE) magnetic resonance (MR) hardly achieves a good imaging performance of arteries and lymph nodes in the breast area. Therefore, a new imaging method is needed for the assessment of breast arteries and lymph nodes. Methods We performed prospective research. The research included 52 patients aged from 25 to 64 between June 2019 and April 2020. The isotropic e-THRIVE sequence scanned in the coronal direction after DCE-THRIVE. Reconstructed images obtained by DCE-THRIVE and the coronal e-THRIVE were compared mainly in terms of the completeness of the lateral thoracic artery, thoracodorsal artery, and lymph nodes. We proposed a criterion for evaluating image quality. According to the criterion, images were assigned a score from 1 to 5 according to the grade from low to high. Two board-certified doctors evaluated images individually, and their average score was taken as the final result. The chi-square test was used to assess the difference. Results The coronal e-THRIVE score is 4.60, which is higher than the DCE-THRIVE score of 3.48, there are significant differences between the images obtained by two sequences (P = 1.2712e−8). According to the score of images, 44 patients (84.61%) had high-quality images on the bilateral breast. Only 3 patients’ (5.77%) images were not ideal on both sides. The improved method is effective for most patients to get better images. Conclusions The proposed coronal e-THRIVE scan can get higher quality reconstruction images than the conventional method to visualize the course of arteries and the distribution of lymph nodes in most patients, which will be helpful for the clinical follow-up treatment.

Whole slide imaging enables scanning entire stained-glass slides with high resolution into digital images for the tissue morphology/molecular pathology assessment and analysis, which has increased in adoption for both clinical and research applications. As an alternative to conventional optical microscopy, lensfree holography imaging, which offers high resolution and a wide field of view (FOV) with digital focus, has been widely used in various types of biomedical imaging. However, accurate colour holographic imaging with pixel super-resolution reconstruction has remained a great challenge due to its coherent characteristic. In this work, we propose a wide-field pixel super-resolution colour lensfree microscopy by performing wavelength scanning pixel super-resolution and phase retrieval simultaneously on the three channels of red, green and blue (RGB), respectively. High-resolution RGB three-channel composite colour image is converted to the YUV space for separating the colour component and the brightness component, keeping the brightness component unchanged as well as enhancing the colour component through average filter, which not only eliminates the common rainbow artifacts of holographic colour reconstruction but also maintains the high-resolution details collected under different colour illuminations. We conducted experiments on the reconstruction of a USAF1951, stained lotus root and red bone marrow smear for performance evaluation of the spatial resolution and colour reconstruction with an imaging FOV >40 mm2.

Noninvasive blood glucose monitoring (NBGM) provides a promising solution for patients with diabetes with the advantages of painless and continuous monitoring. To better characterize the response of glucose to radio-frequency (RF) signals at low frequencies, the conductivity and relative permittivity of aqueous solutions with different glucose concentrations were obtained by the use of an impedance analyzer in the frequency range of 1 kHz to 1 MHz. Furthermore, considering the blood volume pulsation in cardiac cycle, a new approach based on measuring bioimpedance was presented for NBGM in this paper. For this purpose, an inhomogeneous arm model, which consists of three tissue layers (i.e., blood, blood vessel, and other relevant tissues), was proposed to validate the aforementioned approach. Furthermore, the measurements were carried out by means of in vitro experiment and in vivo studies, respectively. The results showed that as the glucose concentration increased, the conductivity of aqueous solutions decreased when the frequency of RF signal was below 1 MHz. However, the relative permittivity was almost insensitive to glucose concentration. The simulation result of the arm model showed that as the glucose concentration increased, the bioimpedance difference of blood volume decreased. This was supported by both in vitro and in vivo experiments. We therefore suggest that the proposed approach for NBGM has potentials in practical applications.

In this paper, an approach to biometric verification based on human body communication (HBC) is presented for wearable devices. For this purpose, the transmission gain S21 of volunteer’s forearm is measured by vector network analyzer (VNA). Specifically, in order to determine the chosen frequency for biometric verification, 1800 groups of data are acquired from 10 volunteers in the frequency range 0.3 MHz to 1500 MHz, and each group includes 1601 sample data. In addition, to achieve the rapid verification, 30 groups of data for each volunteer are acquired at the chosen frequency, and each group contains only 21 sample data. Furthermore, a threshold-adaptive template matching (TATM) algorithm based on weighted Euclidean distance is proposed for rapid verification in this work. The results indicate that the chosen frequency for biometric verification is from 650 MHz to 750 MHz. The false acceptance rate (FAR) and false rejection rate (FRR) based on TATM are approximately 5.79% and 6.74%, respectively. In contrast, the FAR and FRR were 4.17% and 37.5%, 3.37% and 33.33%, and 3.80% and 34.17% using K-nearest neighbor (KNN) classification, support vector machines (SVM), and naive Bayesian method (NBM) classification, respectively. In addition, the running time of TATM is 0.019 s, whereas the running times of KNN, SVM and NBM are 0.310 s, 0.0385 s, and 0.168 s, respectively. Therefore, TATM is suggested to be appropriate for rapid verification use in wearable devices.