3 papers
eess.IV2026
FUGC: Benchmarking Semi-Supervised Learning Methods for Cervical Segmentation
Jieyun Bai, Yitong Tang, Zihao Zhou +36
Accurate segmentation of cervical structures in transvaginal ultrasound (TVS) is critical for assessing the risk of spontaneous preterm birth (PTB), yet the scarcity of labeled dat…
cs.CV2025
Learning Disentangled Stain and Structural Representations for Semi-Supervised Histopathology Segmentation
Ha-Hieu Pham, Nguyen Lan Vi Vu, Thanh-Huy Nguyen +4
Accurate gland segmentation in histopathology images is essential for cancer diagnosis and prognosis. However, significant variability in Hematoxylin and Eosin (H&E) staining and t…
cs.CV2025
HDC: Hierarchical Distillation for Multi-level Noisy Consistency in Semi-Supervised Fetal Ultrasound Segmentation
Tran Quoc Khanh Le, Nguyen Lan Vi Vu, Ha-Hieu Pham +5
Transvaginal ultrasound is a critical imaging modality for evaluating cervical anatomy and detecting physiological changes. However, accurate segmentation of cervical structures re…