activity
20192026
most citedmmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation

12 citations · 41 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ML2026

Conformalized Rate-Adaptive Sensing

Jiawei Yang, Yao Zhang

Many high-resolution imaging systems face the same fundamental question: when have enough measurements been collected to reconstruct an image accurately? We develop Conformalized R…

eess.IV2022★ 12 cited

mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation

Yao Zhang, Nanjun He, Jiawei Yang +6

Accurate brain tumor segmentation from Magnetic Resonance Imaging (MRI) is desirable to joint learning of multimodal images. However, in clinical practice, it is not always possibl…

cs.CV2022★ 11 cited

Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images

Yao Zhang, Jiawei Yang, Yang Liu +6

Purpose: Automated liver tumor segmentation from Computed Tomography (CT) images is a necessary prerequisite in the interventions of hepatic abnormalities and surgery planning. How…

eess.IV2021★ 10 cited

Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation

Yao Zhang, Jiawei Yang, Jiang Tian +4

Liver cancer is one of the most common cancers worldwide. Due to inconspicuous texture changes of liver tumor, contrast-enhanced computed tomography (CT) imaging is effective for t…

eess.IV2020★ 1 cited

Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer

Yao Zhang, Jiawei Yang, Feng Hou +6

Accurate segmentation of cardiac structures can assist doctors to diagnose diseases, and to improve treatment planning, which is highly demanded in the clinical practice. However,…

eess.IV2019

The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge

Nicholas Heller, Fabian Isensee, Klaus H. Maier-Hein +38

There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors a…

eess.IV2019★ 7 cited

Cascaded Volumetric Convolutional Network for Kidney Tumor Segmentation from CT volumes

Yao Zhang, Yixin Wang, Feng Hou +4

Automated segmentation of kidney and tumor from 3D CT scans is necessary for the diagnosis, monitoring, and treatment planning of the disease. In this paper, we describe a two-stag…