most citedKnowledge Distillation with Adaptive Asymmetric Label Sharpening for Semi-supervised Fracture Detection in Chest X-rays

6 citations · 15 across the 10 of their papers we have counts for

collaborators

15 papers

eess.IV2021

Comprehensive and Clinically Accurate Head and Neck Organs at Risk Delineation via Stratified Deep Learning: A Large-scale Multi-Institutional Study

Dazhou Guo, Jia Ge, Xianghua Ye +22

Accurate organ at risk (OAR) segmentation is critical to reduce the radiotherapy post-treatment complications. Consensus guidelines recommend a set of more than 40 OARs in the head…

eess.IV2021

A deep learning pipeline for localization, differentiation, and uncertainty estimation of liver lesions using multi-phasic and multi-sequence MRI

Peng Wang, Yuhsuan Wu, Bolin Lai +9

Objectives: to propose a fully-automatic computer-aided diagnosis (CAD) solution for liver lesion characterization, with uncertainty estimation. Methods: we enrolled 400 patients w…

cs.CV20211 cited

Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT

Xianghua Ye, Dazhou Guo, Chen-kan Tseng +22

Background: The current clinical workflow for esophageal gross tumor volume (GTV) contouring relies on manual delineation of high labor-costs and interuser variability. Purpose: To…

eess.IV2021

SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings

Fengze Liu, Ke Yan, Adam Harrison +8

In this work, we introduce a fast and accurate method for unsupervised 3D medical image registration. This work is built on top of a recent algorithm SAM, which is capable of compu…

eess.IV20213 cited

DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search

Dazhou Guo, Xianghua Ye, Jia Ge +9

Lymph node station (LNS) delineation from computed tomography (CT) scans is an indispensable step in radiation oncology workflow. High inter-user variabilities across oncologists a…

eess.IV2021

Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection

Youbao Tang, Ke Yan, Jinzheng Cai +6

Measuring lesion size is an important step to assess tumor growth and monitor disease progression and therapy response in oncology image analysis. Although it is tedious and highly…