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Rank #231 · 4 unique linked submissions.
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To develop and validate a cone-beam breast CT (CBBCT)-based multiregional radiomics model for identification of lymphovascular invasion (LVI) and fuse it into Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram for predicting axillary lymph node (ALN) met...
High-resolution computed tomography (HRCT) is of growing importance in modern clinical practice. Emerging deep-learning-based CT super-resolution (SR) approaches, particularly those arbitrary-scale SR networks employing implicit neural representation (INR), a...
Conventional cone-beam CT (CBCT) on linear accelerators suffers from limited soft-tissue contrast and quantitative inaccuracy, hindering its use for precision radiotherapy tasks. This study aims to develop and clinically validate a deep learning-based materia...
This study assessed the feasibility and dosimetric quality of uTPS (Shanghai United Imaging Healthcare, version R001) for left-sided breast cancer VMAT planning on dual-layer MLC Accelerators