IEEE Journal of Translational Engineering in Health and Medicine-Jtehm最新文献

{"title":"A Wearable Fluorescence Imaging Device for Intraoperative Identification of Human Brain Tumors","authors":"Mehrana Mohtasebi;Chong Huang;Mingjun Zhao;Siavash Mazdeyasna;Xuhui Liu;Samaneh Rabienia Haratbar;Faraneh Fathi;Jinghong Sun;Thomas Pittman;Guoqiang Yu","doi":"10.1109/JTEHM.2023.3338564","DOIUrl":"https://doi.org/10.1109/JTEHM.2023.3338564","url":null,"abstract":"Malignant glioma (MG) is the most common type of primary malignant brain tumors. Surgical resection of MG remains the cornerstone of therapy and the extent of resection correlates with patient survival. A limiting factor for resection, however, is the difficulty in differentiating the tumor from normal tissue during surgery. Fluorescence imaging is an emerging technique for real-time intraoperative visualization of MGs and their boundaries. However, most clinical grade neurosurgical operative microscopes with fluorescence imaging ability are hampered by low adoption rates due to high cost, limited portability, limited operation flexibility, and lack of skilled professionals with technical knowledge. To overcome the limitations, we innovatively integrated miniaturized light sources, flippable filters, and a recording camera to the surgical eye loupes to generate a wearable fluorescence eye loupe (FLoupe) device for intraoperative imaging of fluorescent MGs. Two FLoupe prototypes were constructed for imaging of Fluorescein and 5-aminolevulinic acid (5-ALA), respectively. The wearable FLoupe devices were tested on tumor-simulating phantoms and patients with MGs. Comparable results were observed against the standard neurosurgical operative microscope (PENTERO® 900) with fluorescence kits. The affordable and wearable FLoupe devices enable visualization of both color and fluorescence images with the same quality as the large and expensive stationary operative microscopes. The wearable FLoupe device allows for a greater range of movement, less obstruction, and faster/easier operation. Thus, it reduces surgery time and is more easily adapted to the surgical environment than unwieldy neurosurgical operative microscopes. Clinical and Translational Impact Statement—The affordable and wearable fluorescence imaging device developed in this study enables neurosurgeons to observe brain tumors with the same clarity and greater flexibility compared to bulky and costly operative microscopes.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"225-232"},"PeriodicalIF":3.4,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10339301","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Treatment of Nocturnal Enuresis Using Miniaturised Smart Mechatronics With Artificial Intelligence","authors":"Kaya Kuru;Darren Ansell;Dave Hughes;Benjamin Jon Watkinson;Fabrizio Gaudenzi;Martin Jones;David Lunardi;Noreen Caswell;Adela Rabella Montiel;Peter Leather;Daniel Irving;Kina Bennett;Corrin McKenzie;Paula Sugden;Carl Davies;Christian Degoede","doi":"10.1109/JTEHM.2023.3336889","DOIUrl":"https://doi.org/10.1109/JTEHM.2023.3336889","url":null,"abstract":"Our study was designed to develop a customisable, wearable, and comfortable medical device – the text so-called “MyPAD” that monitors the fullness of the bladder, triggering an alarm indicating the need to void, in order to prevent badwetting – i.e., treating Nocturnal Enuresis (NE) at the text pre-void stage using miniaturised mechatronics with Artificial Intelligence (AI). The developed features include: multiple bespoke ultrasound (US) probes for sensing, a bespoke electronic device housing custom US electronics for signal processing, a bedside alarm box for processing the echoed pulses and generating alarms, and a phantom to mimic the human body. The validation of the system is conducted on the text tissue-mimicking phantom and volunteers using Bidirectional Long Short-Term Memory Recurrent Neural Networks (Bi-LSTM-RNN) and Reinforcement Learning (RL). A Se value of 99% and a Sp value of 99.5% with an overall accuracy rate of 99.3% are observed. The obtained results demonstrate successful empirical evidence for the viability of the device, both in monitoring bladder expansion to determine voiding need and in reinforcing the continuous learning and customisation of the device for bladder control through consecutive uses. Clinical impact: MyPAD will treat the NE better and efficiently against other techniques currently used (e.g., post-void alarms) and will i) replace those techniques quickly considering sufferers’ condition while being treated by other approaches, and ii) enable children to gain control of incontinence over time and consistently have dry nights. Category: Early/Pre-Clinical Research","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"204-214"},"PeriodicalIF":3.4,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10328832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138485029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mixed Reality and Artificial Intelligence: A Holistic Approach to Multimodal Visualization and Extended Interaction in Knee Osteotomy","authors":"Andrea Moglia;Luca Marsilio;Matteo Rossi;Maria Pinelli;Emanuele Lettieri;Luca Mainardi;Alfonso Manzotti;Pietro Cerveri","doi":"10.1109/JTEHM.2023.3335608","DOIUrl":"https://doi.org/10.1109/JTEHM.2023.3335608","url":null,"abstract":"Objective: Recent advancements in augmented reality led to planning and navigation systems for orthopedic surgery. However little is known about mixed reality (MR) in orthopedics. Furthermore, artificial intelligence (AI) has the potential to boost the capabilities of MR by enabling automation and personalization. The purpose of this work is to assess Holoknee prototype, based on AI and MR for multimodal data visualization and surgical planning in knee osteotomy, developed to run on the HoloLens 2 headset. Methods: Two preclinical test sessions were performed with 11 participants (eight surgeons, two residents, and one medical student) executing three times six tasks, corresponding to a number of holographic data interactions and preoperative planning steps. At the end of each session, participants answered a questionnaire on user perception and usability. Results: During the second trial, the participants were faster in all tasks than in the first one, while in the third one, the time of execution decreased only for two tasks (“Patient selection” and “Scrolling through radiograph”) with respect to the second attempt, but without statistically significant difference (respectively \u0000<inline-formula> <tex-math>$p$ </tex-math></inline-formula>\u0000 = 0.14 and \u0000<inline-formula> <tex-math>$p$ </tex-math></inline-formula>\u0000 = 0.13, \u0000<inline-formula> <tex-math>$p &lt; 0.05$ </tex-math></inline-formula>\u0000). All subjects strongly agreed that MR can be used effectively for surgical training, whereas 10 (90.9%) strongly agreed that it can be used effectively for preoperative planning. Six (54.5%) agreed and two of them (18.2%) strongly agreed that it can be used effectively for intraoperative guidance. Discussion/Conclusion: In this work, we presented Holoknee, the first holistic application of AI and MR for surgical planning for knee osteotomy. It reported promising results on its potential translation to surgical training, preoperative planning, and surgical guidance. Clinical and Translational Impact Statement - Holoknee can be helpful to support surgeons in the preoperative planning of knee osteotomy. It has the potential to impact positively the training of the future generation of residents and aid surgeons in the intraoperative stage.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"279-290"},"PeriodicalIF":3.4,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10325506","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139676277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inertial Measurement Unit-Based Romberg Test for Assessing Adults With Vestibular Hypofunction","authors":"Kuan-Chung Ting;Yu-Chieh Lin;Chia-Tai Chan;Tzong-Yang Tu;Chun-Che Shih;Kai-Chun Liu;Yu Tsao","doi":"10.1109/JTEHM.2023.3334238","DOIUrl":"https://doi.org/10.1109/JTEHM.2023.3334238","url":null,"abstract":"This work aims to explore the utility of wearable inertial measurement units (IMUs) for quantifying movement in Romberg tests and investigate the extent of movement in adults with vestibular hypofunction (VH). A cross-sectional study was conducted at an academic tertiary medical center between March 2021 and April 2022. Adults diagnosed with unilateral vestibular hypofunction (UVH) or bilateral vestibular hypofunction (BVH) were enrolled in the VH group. Healthy controls (HCs) were recruited from community or outpatient clinics. The IMU-based instrumented Romberg and tandem Romberg tests on the floor were applied to both groups. The primary outcomes were kinematic body metrics (maximum acceleration [ACC], mean ACC, root mean square [RMS] of ACC, and mean sway velocity [MV]) along the medio-lateral (ML), cranio-caudal (CC), and antero-posterior (AP) axes. A total of 31 VH participants (mean age, 33.48 [SD 7.68] years; 19 [61%] female) and 31 HCs (mean age, 30.65 [SD 5.89] years; 18 [58%] female) were recruited. During the eyes-closed portion of the Romberg test, VH participants demonstrated significantly higher maximum ACC and increased RMS of ACC in head movement, as well as higher maximum ACC in pelvic movement along the ML axis. In the same test condition, individuals with BVH exhibited notably higher maximum ACC and RMS of ACC along the ML axis in head and pelvic movements compared with HCs. Additionally, BVH participants exhibited markedly increased maximum ACC along the ML axis in head movement during the eyes-open portion of the tandem Romberg test. Conversely, no significant differences were found between UVH participants and HCs in the assessed parameters. The instrumented Romberg and tandem Romberg tests characterized the kinematic differences in head, pelvis, and ankle movement between VH and healthy adults. The findings suggest that these kinematic body metrics can be useful for screening BVH and can provide goals for vestibular rehabilitation.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"245-255"},"PeriodicalIF":3.4,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10322744","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139034303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Navigation Device for Precise Percutaneous Placement of the Guidewire in Femoral Neck Fracture Cannulated Screw Fixation Surgery","authors":"Yutao Cui;Guangkai Ren;Chuangang Peng;Baoming Yuan;Dankai Wu","doi":"10.1109/JTEHM.2023.3332453","DOIUrl":"https://doi.org/10.1109/JTEHM.2023.3332453","url":null,"abstract":"The accuracy of screw placement is a key factor for the stability of the cannulated screws used in the fixation of femoral neck fractures. In this study we designed a navigation device for ensuring the screw reaches the ideal position for optimal fixation. From March 2019 to September 2020, 66 patients with femoral neck fracture were enrolled and divided into 2 groups, one group was treated using the traditional free-hand cannulated screw fixation and the other using the new navigation device with assisted fixation. The effectiveness of the 2 methods was compared based on surgery duration, intraoperative bleeding, number of fluoroscopic examination and guidewire insertion attempts, screw parallelism, and effective fixation area. Fracture healing, complications and hip joint function were assessed after operation. The new navigation device reduced the duration of surgery without causing additional intraoperative bleeding, and significantly reduced number of fluoroscopy examination and guidewire insertion attempts (4.00±1.58 vs. 6.09±1.94 with traditional surgery). The accuracy of screw implantation was improved, as demonstrated by increased screw parallelism (0.71±0.57° vs. 1.66 ±1.01° with traditional surgery) and higher effective fixed area (64.88±10.52 vs. 58.61±9.19 mm2 with traditional surgery). In the postoperative follow-up, except for one case of femoral head necrosis and one case of bone nonunion in the traditional surgical group, the other patients showed fracture healing. There was no significant difference in hip joint function between the 2 groups. The new navigation device enables rapid and accurate guidewire positioning for cannulated screw fixation through simple operation procedures, resulting in good prospect for clinical transformation.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"162-170"},"PeriodicalIF":3.4,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10319461","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138485009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying Machine Learning and Point-Set Registration to Automatically Measure the Severity of Spinal Curvature on Radiographs","authors":"Jason Wong;Marek Reformat;Edmond Lou","doi":"10.1109/JTEHM.2023.3332618","DOIUrl":"10.1109/JTEHM.2023.3332618","url":null,"abstract":"Objective: Measuring the severity of the lateral spinal curvature, or Cobb angle, is critical for monitoring and making treatment decisions for children with adolescent idiopathic scoliosis (AIS). However, manual measurement is time-consuming and subject to human error. Therefore, clinicians seek an automated measurement method to streamline workflow and improve accuracy. This paper reports on a novel machine learning algorithm of cascaded convolutional neural networks (CNN) to measure the Cobb angle on spinal radiographs automatically. Methods: The developed method consisted of spinal column segmentation using a CNN, vertebra localization and segmentation using iterative vertebra body location coupled with another CNN, point-set registration to correct vertebra segmentations, and Cobb angle measurement using the final segmentations. Measurement performance was evaluated with the circular mean absolute error (CMAE) and percentage within clinical acceptance (\u0000<inline-formula> <tex-math>$le 5^{circ }$ </tex-math></inline-formula>\u0000) between automatic and manual measurements. Analysis was separated by curve severity to identify any potential systematic biases using independent samples Student’s t-tests. Results: The method detected 346 of the 352 manually measured Cobb angles (98%), with a CMAE of 2.8° and 91% of measurements within the 5° clinical acceptance. No statistically significant differences were found between the CMAEs of mild (\u0000<inline-formula> <tex-math>$ &lt; 25^{circ }$ </tex-math></inline-formula>\u0000), moderate (25°-45°), and severe (\u0000<inline-formula> <tex-math>$ge 45^{circ }$ </tex-math></inline-formula>\u0000) groups. The average measurement time per radiograph was 17.7±10.2s, improving upon the estimated average of 30s it takes an experienced rater to measure. Additionally, the algorithm outputs segmentations with the measurement, allowing clinicians to interpret measurement results. Discussion/Conclusion: The developed method measured Cobb angles on radiographs automatically with high accuracy, quick measurement time, and interpretability, suggesting clinical feasibility.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"151-161"},"PeriodicalIF":3.4,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10318103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135704997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Registration Sanity Check for AR-guided Surgical Interventions: Experience From Head and Face Surgery","authors":"Sara Condino;Fabrizio Cutolo;Marina Carbone;Laura Cercenelli;Giovanni Badiali;Nicola Montemurro;Vincenzo Ferrari","doi":"10.1109/JTEHM.2023.3332088","DOIUrl":"10.1109/JTEHM.2023.3332088","url":null,"abstract":"Achieving and maintaining proper image registration accuracy is an open challenge of image-guided surgery. This work explores and assesses the efficacy of a registration sanity check method for augmented reality-guided navigation (AR-RSC), based on the visual inspection of virtual 3D models of landmarks. We analyze the AR-RSC sensitivity and specificity by recruiting 36 subjects to assess the registration accuracy of a set of 114 AR images generated from camera images acquired during an AR-guided orthognathic intervention. Translational or rotational errors of known magnitude up to ±1.5 mm/±15.5°, were artificially added to the image set in order to simulate different registration errors. This study analyses the performance of AR-RSC when varying (1) the virtual models selected for misalignment evaluation (e. g., the model of brackets, incisor teeth, and gingival margins in our experiment), (2) the type (translation/rotation) of registration error, and (3) the level of user experience in using AR technologies. Results show that: 1) the sensitivity and specificity of the AR-RSC depends on the virtual models (globally, a median true positive rate of up to 79.2% was reached with brackets, and a median true negative rate of up to 64.3% with incisor teeth), 2) there are error components that are more difficult to identify visually, 3) the level of user experience does not affect the method. In conclusion, the proposed AR-RSC, tested also in the operating room, could represent an efficient method to monitor and optimize the registration accuracy during the intervention, but special attention should be paid to the selection of the AR data chosen for the visual inspection of the registration accuracy.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"258-267"},"PeriodicalIF":3.4,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10315237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135659363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the Editor: “How Can Biomedical Engineers Help Empower Individuals With Intellectual Disabilities? The Potential Benefits and Challenges of AI Technologies to Support Inclusivity and Transform Lives”","authors":"Alessandro Di Nuovo","doi":"10.1109/JTEHM.2023.3331977","DOIUrl":"10.1109/JTEHM.2023.3331977","url":null,"abstract":"The rapid advancement of Artificial Intelligence (AI) is transforming healthcare and daily life, offering great opportunities but also posing ethical and societal challenges. To ensure AI benefits all individuals, including those with intellectual disabilities, the focus should be on adaptive technology that can adapt to the unique needs of the user. Biomedical engineers have an interdisciplinary background that helps them to lead multidisciplinary teams in the development of human-centered AI solutions. These solutions can personalize learning, enhance communication, and improve accessibility for individuals with intellectual disabilities. Furthermore, AI can aid in healthcare research, diagnostics, and therapy. The ethical use of AI in healthcare and the collaboration of AI with human expertise must be emphasized. Public funding for inclusive research is encouraged, promoting equity and economic growth while empowering those with intellectual disabilities in society.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"256-257"},"PeriodicalIF":3.4,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10314515","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135562888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated, Vision-Based Goniometry and Range of Motion Calculation in Individuals With Suspected Ehlers-Danlos Syndromes/Generalized Hypermobility Spectrum Disorders: A Comparison of Pose-Estimation Libraries to Goniometric Measurements","authors":"Andrea Sabo;Nimish Mittal;Amol Deshpande;Hance Clarke;Babak Taati","doi":"10.1109/JTEHM.2023.3327691","DOIUrl":"10.1109/JTEHM.2023.3327691","url":null,"abstract":"Generalized joint hypermobility (GJH) often leads clinicians to suspect a diagnosis of Ehlers Danlos Syndrome (EDS), but it can be difficult to objectively assess. Video-based goniometry has been proposed to objectively estimate joint range of motion in hyperextended joints. As part of an exam of joint hypermobility at a specialized EDS clinic, a mobile phone was used to record short videos of 97 adults (89 female, 35.0 ± 9.9 years old) undergoing assessment of the elbows, knees, shoulders, ankles, and fifth fingers. Five body keypoint pose-estimation libraries (AlphaPose, Detectron, MediaPipe-Body, MoveNet – Thunder, OpenPose) and two hand keypoint pose-estimation libraries (AlphaPose, MediaPipe-Hands) were used to geometrically calculate the maximum angle of hyperextension or hyperflexion of each joint. A custom domain-specific model with a MobileNet-v2 backbone finetuned on data collected as part of this study was also evaluated for the fifth finger movement. Spearman’s correlation was used to analyze the angles calculated from the tracked joint positions, the angles calculated from manually annotated keypoints, and the angles measured using a goniometer. Moderate correlations between the angles estimated using pose-tracked keypoints and the goniometer measurements were identified for the elbow (rho =.722; Detectron), knee (rho =.608; MoveNet – Thunder), shoulder (rho =.632; MoveNet – Thunder), and fifth finger (rho =.786; custom model) movements. The angles estimated from keypoints predicted by open-source libraries at the ankles were not significantly correlated with the goniometer measurements. Manually annotated angles at the elbows, knees, shoulders, and fifth fingers were moderately to strongly correlated to goniometer measurements but were weakly correlated for the ankles. There was not one pose-estimation library which performed best across all joints, so the library of choice must be selected separately for each joint of interest. This work evaluates several pose-estimation models as part of a vision-based system for estimating joint angles in individuals with suspected joint hypermobility. Future applications of the proposed system could facilitate objective assessment and screening of individuals referred to specialized EDS clinics.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"140-150"},"PeriodicalIF":3.4,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10309843","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135501586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TTN: Topological Transformer Network for Automated Coronary Artery Branch Labeling in Cardiac CT Angiography","authors":"Yuyang Zhang;Gongning Luo;Wei Wang;Shaodong Cao;Suyu Dong;Daren Yu;Xiaoyun Wang;Kuanquan Wang","doi":"10.1109/JTEHM.2023.3329031","DOIUrl":"10.1109/JTEHM.2023.3329031","url":null,"abstract":"Objective: Existing methods for automated coronary artery branch labeling in cardiac CT angiography face two limitations: 1) inability to model overall correlation of branches, since differences between branches cannot be captured directly. 2) a serious class imbalance between main and side branches. Methods and procedures: Inspired by the application of Transformer in sequence data, we propose a topological Transformer network (TTN), which solves the vessel branch labeling from a novel perspective of sequence labeling learning. TTN detects differences between branches by establishing their overall correlation. A topological encoding that represents the positions of vessel segments in the artery tree, is proposed to assist the model in classifying branches. Also, a segment-depth loss is introduced to solve the class imbalance between main and side branches. Results: On a dataset with 325 CCTA, our method obtains the best overall result on all branches, the best result on side branches, and a competitive result on main branches. Conclusion: TTN solves two limitations in existing methods perfectly, thus achieving the best result in coronary artery branch labeling task. It is the first Transformer based vessel branch labeling method and is notably different from previous methods. Clinical impact: This Pre-Clinical Research can be integrated into a computer-aided diagnosis system to generate cardiovascular disease diagnosis report, assisting clinicians in locating the atherosclerotic plaques.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"12 ","pages":"129-139"},"PeriodicalIF":3.4,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10304172","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135319101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}