A novel 3D UXFormer model is introduced that combines the 3D UNET and Vision Transformer (ViT) through a dual-branch structure, capitalizing on the 3D UNET's local feature extraction prowess and ViT's global feature-capturing ability.
Accurate breast cancer classification in dynamic contrast-enhanced (DCE) magnetic resonance imaging requires effective integration of volumetric morphology and temporal contrast-enhancement kinetics. In this study, we evaluate a multi-temporal 3D framework for three-class breast classification (normal, benign, malignan...
T. Nguyen, Hung Le Minh· Biomedical engineering and p...· 0 citations
A 3D U-Net-based segmentation framework, NeuroFocusNet, which synchronizes spatial attention, channel recalibration, and attention-gated skip connections within a single volumetric encoder-decoder model is proposed, which is encouraging when considering the feasibility of using NeuroFocusNet as a technically promising...
Faizan Ullah, Z. Abbas, Sergo Gegechkori et al.· IEEE Access· 0 citations
Its high multi-center adaptability and stability in small-lesion segmentation make it suitable for cross-institutional promotion, providing reliable anatomical references for prognosis assessment, doctor-patient communication, and rehabilitation monitoring.
Jia-Tong Wang, Hong-Xun Cui, Yong-Hui Liu et al.· 0 citations
Objective. Accurate Ultrasound (US) prostate cancer (PCa) segmentation images hold significant value for organ interventional guidance and clinical disease diagnosis. However, this task still poses substantial challenges. The main obstacles include blurred or incomplete boundaries separating PCa from adjacent soft tiss...
Yu Wang, Li-Li Wang, Cai-Shan Wang et al.· Physics in Medicine and Biol...· 0 citations
Background Automated segmentation of glioma subregions on multiparametric MRI can be improved by changing either the network architecture or the information presented to the network. These two design levers are usually studied together, which makes their individual contributions difficult to see. We present an integrat...
Accurate lesion segmentation in breast ultrasound images is crucial for early diagnosis and treatment planning, yet remains highly challenging due to inherent imaging characteristics, including low signal-to-noise ratio, speckle noise artifacts, blurred boundaries, and significant inter-lesion appearance variability. F...
Ya-Dong Lan, Yu Liu, Zai-Yi Liu et al.· Conference on Advanced Algor...· 0 citations
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