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20242026
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cs.CV2026

KOAL: Knowledge-Driven Prostate Cancer Grading with Ordinal-Aware Learning

Zheng Guo, Jiaqi Cui, Haocheng Xiong +5

Non-invasive prediction of Gleason Grade Group (GGG) in prostate cancer using multiparametric MRI (mpMRI) is clinically vital for reducing unnecessary biopsies. Existing GGG predic…

cs.CV2025

BASIC: Semi-supervised Multi-organ Segmentation with Balanced Subclass Regularization and Semantic-conflict Penalty

Zhenghao Feng, Lu Wen, Yuanyuan Xu +4

Semi-supervised learning (SSL) has shown notable potential in relieving the heavy demand of dense prediction tasks on large-scale well-annotated datasets, especially for the challe…

cs.CV2024

BTMuda: A Bi-level Multi-source unsupervised domain adaptation framework for breast cancer diagnosis

Yuxiang Yang, Xinyi Zeng, Pinxian Zeng +4

Deep learning has revolutionized the early detection of breast cancer, resulting in a significant decrease in mortality rates. However, difficulties in obtaining annotations and hu…

cs.CV2024

Alleviating Class Imbalance in Semi-supervised Multi-organ Segmentation via Balanced Subclass Regularization

Zhenghao Feng, Lu Wen, Binyu Yan +2

Semi-supervised learning (SSL) has shown notable potential in relieving the heavy demand of dense prediction tasks on large-scale well-annotated datasets, especially for the challe…

cs.CV2024

ARANet: Attention-based Residual Adversarial Network with Deep Supervision for Radiotherapy Dose Prediction of Cervical Cancer

Lu Wen, Wenxia Yin, Zhenghao Feng +3

Radiation therapy is the mainstay treatment for cervical cancer, and its ultimate goal is to ensure the planning target volume (PTV) reaches the prescribed dose while reducing dose…

cs.CV2024

Learning with Alignments: Tackling the Inter- and Intra-domain Shifts for Cross-multidomain Facial Expression Recognition

Yuxiang Yang, Lu Wen, Xinyi Zeng +4

Facial Expression Recognition (FER) holds significant importance in human-computer interactions. Existing cross-domain FER methods often transfer knowledge solely from a single lab…