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Highlights • It is difficult to visualize extra-hepatic biliary anatomy clearly because of long-presence of ICG in liver when administered intravenously. • Intracholecystic ICG injection illuminates extra-hepatic biliary tree preferentially thus reducing background hepatic noise. • Surgeons can experience more satisfaction with the use of fluorescent cholangiography during laparoscopic cholecystectomy when the intracystic route of ICG administration is utilized., Introduction The utility of intracystic administration of indocyanine green for near-infrared fluorescent cholangiography in acute calculous cholecystitis initially treated with percutaneous transhepatic gallbladder drainage (PTGBD) was described in this report. Presentation of case Two cases who underwent near-infrared fluorescent cholangiography guided interval laparoscopic cholecystectomy two weeks post-PTGBD were studied retrospectively. Both patients were diagnosed with moderate acute calculous cholecystitis based on diagnostic criteria of the Tokyo guidelines. Two routes of indocyanine green administration were utilized during surgery, first through direct intracystic administration through PTGBD tube (5 ml of 12.5 mg ICG) to achieve critical view of safety and then intravenous administration (1 ml of 2.5 mg ICG) to visualize cystic artery. Discussion Both patients had critical view of safety visualized clearly with ICG with the operation time of 84 and 125 min in cases 1 and 2, respectively without any intra or postoperative complications. Conclusion In comparison with intravenous ICG administration, trans-PTGBD ICG route can provide better signal-to-noise ratio by avoiding hepatic fluorescence and thus increasing the bile duct to liver contrast. However, ICG may enter the lymphatic system through necrotic and inflammatory gallbladder mucosa, of which lymph spillage during gallbladder dissection can obscure the fluorescent view.

Objective: The objective of this study was to evaluate augmented reality-assisted single-incision laparoscopic adrenalectomy (AR-SILA) and compare with pure SILA. Materials and Methods: Between January 2009 and March 2012, a total of 19 patients had received SILA. Eight cases were AR-SILA and the others were pure SILA. Results: Eight AR-SILA procedures and 11 SILA were successfully completed. There was no significant difference between the two groups in terms of age, body mass index, and tumor size. Operative times were shorter in the AR-SILA group (102.5 ± 12.8 vs. 150.9 ± 46.3, P = 0.005). The mean blood loss in the AR-SILA group was slightly less than that in the SILA group (60.0 ± 25.6 vs. 109.1 ± 80.1, P = 0.129). There was neither postoperative mortality nor morbidity at the time of discharge and during follow-up. Conclusion: AR-SILA provides important intraoperative information for surgeons to recognize where the pathological lesions and vessels are located beyond the surgeon's direct vision. It made SILA safer and easier.

Endoscopic surgery causes less tissue injury compared to open surgical techniques, thus promoting more rapid recuperation and reduced post-operative pain. Endoscopy, however, allows the surgeon to ...

In USG-guided interventional procedures, the surgeons need to mentally register the reference data set (computed tomography [CT] or magnetic resonance [MR] images), and the working data set of USG (real-time). This study presents a system to combine real time USG information with preoperative 3D CT virtual model using landmark registration. The future goal of this system is to apply for radiofrequency needle tracking during the surgery.

Sub-surface information during a laparoscopic surgery is captured with a near infrared imaging where the tissue is highlighted with the help of an indocyanine dye injected to the patient before the surgery. The surgeons can use such system during the surgery, however, they need to swap the light source between infra-red and the white light to complete the surgery. Swapping the light source causes inconvenience and increase in the time of the surgery. The current study aims to develop a method for superimposing and tracking the infrared imagery on the laparoscopic video acquired under white light. In this study, the infrared imagery was captured and registered to one of the white light imagery from the endoscope video using a 2D image registration technique. The registration technique was based on maximization of mutual information between two images. The edges on the registered infrared image was detected using canny edge detection algorithm. A homography matrix between consecutive video frames under white light was calculated after characteristic feature point detection and matching. The homography matrix was applied on the registered infrared image (only edge) and a new registered edge image was generated. The process continued for every new frame of the video under white light. The system was applied with a video acquisition rate of 20 frames per second. The system needs to be evaluated for its influence on the time of surgery.

An expanding mosaic view is one of the possible solutions for narrow field of view during endoscopic surgery. The current work presents a system to create an expanding mosaic view of the video during laparoscopy where the laparoscope is held and moved by a customized robot arm.

This paper presents a technique that generates rough depth maps from laparoscopy camera using feature tracking techniques for depth sampling. The method is applicable to single laparoscopy video images through local motion cues to improve the inferred depth maps. The feature tracking is used to ensure temporal depth consistency, such as SURF. The results show that the proposed methods significantly improve the depth estimation for laparoscopy surgery. The technique can be used to convert a 2D laparoscopy video into stereo for 3D visualization, and it demonstrates this through a laparoscopy surgery video, including results of surgical instruments.

Pulmonary edema, i.e. excess of extravascular fluid in lungs, is a common manifestation of various clinical conditions. Although the etiology of the pulmonary edema is deduced with the help of history, physical examination and various biochemical and radiological investigations, computer aided evaluation of pulmonary edema will be helpful for physicians in determining the course of management for the condition. In this study we present texture analysis of chest x-ray, using Gabor filter and one of the machine learning techniques, Support Vector Machine (SVM), to distinguish the normal chest x-ray from the chest x-ray of pulmonary edema. This is an initial step towards computer aided quantitative assessment of the pulmonary edema using chest x-ray.

Laparoscopic surgery is indispensable from the current surgical procedures. It uses an endoscope system of camera and light source, and surgical instruments which pass through the small incisions on the abdomen of the patients undergoing laparoscopic surgery. Conventional laparoscope (endoscope) systems produce 2D colored video images which do not provide surgeons an actual depth perception of the scene. In this work, the problem was formulated as synthesizing a stereo image of the monocular (conventional) laparoscope image by incorporating into them the depth information from a 3D CT model. Various algorithms of the computer vision including the algorithms for the feature detection, matching and tracking in the video frames, and for the reconstruction of 3D shape from shading in the 2D laparoscope image were combined for making the system. The current method was applied to the laparoscope video at the rate of up to 5 frames per second to visualize its stereo video. A correlation was investigated between the depth maps calculated with our method with those from the shape from shading algorithm. The correlation coefficients between the depth maps were within the range of 0.70-0.95 (P

This paper presents an advanced augmented reality system for spinal surgery assistance, and develops entry-point guidance prior to vertebroplasty spinal surgery. Based on image-based marker detection and tracking, the proposed camera-projector system superimposes pre-operative 3-D images onto patients. The patients' preoperative 3-D image model is registered by projecting it onto the patient such that the synthetic 3-D model merges with the real patient image, enabling the surgeon to see through the patients' anatomy. The proposed method is much simpler than heavy and computationally challenging navigation systems, and also reduces radiation exposure. The system is experimentally tested on a preoperative 3D model, dummy patient model and animal cadaver model. The feasibility and accuracy of the proposed system is verified on three patients undergoing spinal surgery in the operating theater. The results of these clinical trials are extremely promising, with surgeons reporting favorably on the reduced time of finding a suitable entry point and reduced radiation dose to patients.

In this paper, we present a system for spinal cord and nerves segmentation from STIR-MRI. We propose an user interactive segmentation method for 3D images, which is extended from the 2D random walker algorithm and implemented with a slice-section strategy. After obtaining the 3D segmentation result, we build the 3D spinal cord and nerves model for each view using VTK, which is an open-source, freely available software. Then we obtain the point cloud of the spinal cord and nerves surface by registering the three surface models constructed from three STIR-MRI images of different directions. In the experimental results, we show the 3D segmentation results of spinal cord and nerves from the STIR-MRI (Short Tau Inversion Recovery - Magnetic Resonance Imaging)images in three different views, and also display the reconstructed 3D surface model.

Surgical procedures have undergone considerable advancement during the last few decades. More recently, the availability of some imaging methods intraoperatively has added a new dimension to minimally invasive techniques. Augmented reality in surgery has been a topic of intense interest and research. Augmented reality involves usage of computer vision algorithms on video from endoscopic cameras or cameras mounted in the operating room to provide the surgeon additional information that he or she otherwise would have to recognize intuitively. One of the techniques combines a virtual preoperative model of the patient with the endoscope camera using natural or artificial landmarks to provide an augmented reality view in the operating room. The authors’ approach is to provide this with the least number of changes to the operating room. Software architecture is presented to provide interactive adjustment in the registration of a three-dimensional (3D) model and endoscope video. Augmented reality including adrenalectomy, ureteropelvic junction obstruction, and retrocaval ureter and pancreas was used to perform 12 surgeries. The general feedback from the surgeons has been very positive not only in terms of deciding the positions for inserting points but also in knowing the least change in anatomy. The approach involves providing a deformable 3D model architecture and its application to the operating room. A 3D model with a deformable structure is needed to show the shape change of soft tissue during the surgery. The software architecture to provide interactive adjustment in registration of the 3D model and endoscope video with adjustability of every 3D model is presented.