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Delving Aleatoric Uncertainty in Medical Image Segmentation via Vision Foundation Models
Ruiyang Li, Fang Liu, Licheng Jiao +8
Medical image segmentation supports clinical workflows by precisely delineating anatomical structures and lesions. However, medical image datasets medical image datasets suffer fro…
Human Gaze-based Dual Teacher Guidance Learning for Semi-Supervised Medical Image Segmentation
Rongjun Ge, Chong Wang, Yuxin Liu +10
In the field of medical image segmentation, the scarcity of labeled data poses a major challenge for existing models to accurately perceive target regions. Compared with manual ann…
VIVID-Med: LLM-Supervised Structured Pretraining for Deployable Medical ViTs
Xiyao Wang, Xiaoyu Tan, Yang Dai +3
Vision-language pretraining has driven significant progress in medical image analysis. However, current methods typically supervise visual encoders using one-hot labels or free-for…
Beyond Benchmarks of IUGC: Rethinking Requirements of Deep Learning Methods for Intrapartum Ultrasound Biometry from Fetal Ultrasound Videos
Jieyun Bai, Zihao Zhou, Yitong Tang +60
A substantial proportion (45\%) of maternal deaths, neonatal deaths, and stillbirths occur during the intrapartum phase, with a particularly high burden in low- and middle-income c…