IEEE transactions on pattern analysis and machine intelligence
Mar 6, 2025
Recovering whole-body mesh by inferring the abstract pose and shape parameters from visual content can obtain 3D bodies with realistic structures. However, the inferring process is highly non-linear and suffers from image-mesh misalignment, resulting...
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...
OBJECTIVE: Surface-based three-dimensional (3D) cephalometry provides detailed clinical information for the analysis of craniofacial structures. This study aimed to develop an automated 3D surface cephalometry system using mesh fitting based on landm...
Recognizing human activities from motion data is a complex task in computer vision, involving the recognition of human behaviors from sequences of 3D motion data. These activities encompass successive body part movements, interactions with objects, o...
PURPOSE: Lumbosacral nerve root anomalies are relatively rare but can be a risk factor for intraoperative nerve injury. However, it is often difficult to evaluate them with preoperative imaging. We developed a software that automatically generates th...
PURPOSE: With the increasing utilization of endoscopic approaches for primary benign orbital tumor (PBOT) surgery, otolaryngologists and ophthalmologists are challenged with determining candidacy for endoscopic resection based on preoperative imaging...
BACKGROUND: Anterior cruciate ligament (ACL) reconstruction is a widely performed procedure for ACL injury, but there are several factors which may lead to re-rupture or clinical failure. An intercondylar notch (or fossa) that is narrower may increas...
In recent years, generating 3D human models from images has gained significant attention in 3D human reconstruction. However, deploying large neural network models in practical applications remains challenging, particularly on resource-constrained ed...
BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, particularly challenging due to the evolving nature of tissue contrasts in the early months of life. The difficulty increases as gray matter (GM) and wh...
UNLABELLED: is a comparative analysis of algorithms for segmentation of three-dimensional OCT images of human skin using neural networks based on U-Net architecture when training the model on two-dimensional and three-dimensional data.
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