MS-KD: Multi-Organ Segmentation with Multiple Binary-Labeled Datasets

no code implementations • 5 Aug 2021 • Shixiang Feng, YuHang Zhou, Xiaoman Zhang, Ya zhang, Yanfeng Wang

A novel Multi-teacher Single-student Knowledge Distillation (MS-KD) framework is proposed, where the teacher models are pre-trained single-organ segmentation networks, and the student model is a multi-organ segmentation network.

Knowledge Distillation Organ Segmentation +1

Uncertainty-aware Incremental Learning for Multi-organ Segmentation

no code implementations • 9 Mar 2021 • YuHang Zhou, Xiaoman Zhang, Shixiang Feng, Ya zhang, Yanfeng

Specifically, given a pretrained $K$ organ segmentation model and a new single-organ dataset, we train a unified $K+1$ organ segmentation model without accessing any data belonging to the previous training stages.

Ethics Incremental Learning +3

Two-Stream Compare and Contrast Network for Vertebral Compression Fracture Diagnosis

no code implementations • 13 Oct 2020 • Shixiang Feng, Beibei Liu, Ya zhang, Xiaoyun Zhang, Yuehua Li

In this paper, we explore to model VCFs diagnosis as a three-class classification problem, i. e. normal vertebrae, benign VCFs, and malignant VCFs.

Classification General Classification +2

SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation

no code implementations • 13 Oct 2020 • Xiaoman Zhang, Shixiang Feng, YuHang Zhou, Ya zhang, Yanfeng Wang

We demonstrate the effectiveness of our methods on two downstream tasks: i) Brain tumor segmentation, ii) Pancreas tumor segmentation.

Brain Tumor Segmentation Segmentation +3