60 citations · 100 across the 8 of their papers we have counts for
8 papers
Leveraging Global Binary Masks for Structure Segmentation in Medical Images
Mahdieh Kazemimoghadam, Zi Yang, Lin Ma +3
Deep learning (DL) models for medical image segmentation are highly influenced by intensity variations of input images and lack generalization due to primarily utilizing pixels' in…
Registration-Guided Deep Learning Image Segmentation for Cone Beam CT-based Online Adaptive Radiotherapy
Lin Ma, Weicheng Chi, Howard E. Morgan +8
Adaptive radiotherapy (ART), especially online ART, effectively accounts for positioning errors and anatomical changes. One key component of online ART is accurately and efficientl…
Volumetric dose extension for isodose tuning
Lin Ma, Mingli Chen, Xuejun Gu +1
Purpose: To develop a model to generate volumetric dose distribution from two isodose surfaces (iso-surfaces), and to interactively tune dose distribution by iso-surface dragging.…
Generalizability of deep learning based fluence map prediction as an inverse planning approach
Lin Ma, Mingli Chen, Xuejun Gu +1
Deep learning-based fluence map prediction(DL-FMP) method has been reported in the literature, which generated fluence maps for desired dose by deep neural network(DNN)-based inver…
Robustness study of noisy annotation in deep learning based medical image segmentation
Shaode Yu, Erlei Zhang, Junjie Wu +6
Partly due to the use of exhaustive-annotated data, deep networks have achieved impressive performance on medical image segmentation. Medical imaging data paired with noisy annotat…
Breast Ultrasound Computer-Aided Diagnosis Using Structure-Aware Triplet Path Networks
Erlei Zhang, Zi Yang, Stephen Seiler +3
Breast ultrasound (US) is an effective imaging modality for breast cancer detec-tion and diagnosis. The structural characteristics of breast lesion play an im-portant role in Compu…
BIRADS Features-Oriented Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis
Erlei Zhang, Stephen Seiler, Mingli Chen +2
Breast ultrasound (US) is an effective imaging modality for breast cancer detection and diagnosis. US computer-aided diagnosis (CAD) systems have been developed for decades and hav…
Towards automated patient data cleaning using deep learning: A feasibility study on the standardization of organ labeling
Timothy Rozario, Troy Long, Mingli Chen +2
Data cleaning consumes about 80% of the time spent on data analysis for clinical research projects. This is a much bigger problem in the era of big data and machine learning in the…