260 citations · 650 across the 16 of their papers we have counts for
10 papers · 1 filter
Loss Ensembles for Extremely Imbalanced Segmentation
Jun Ma
This short paper briefly presents our methodology details of automatic intracranial aneurysms segmentation from brain MR scans. We use ensembles of multiple models trained from dif…
Exploring Large Context for Cerebral Aneurysm Segmentation
Jun Ma, Ziwei Nie
Automated segmentation of aneurysms from 3D CT is important for the diagnosis, monitoring, and treatment planning of the cerebral aneurysm disease. This short paper briefly present…
Cascaded Framework for Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI
Jun Ma
Automatic evaluation of myocardium and pathology plays an important role in the quantitative analysis of patients suffering from myocardial infarction. In this paper, we present a…
Combining CNN and Hybrid Active Contours for Head and Neck Tumor Segmentation in CT and PET images
Jun Ma, Xiaoping Yang
Automatic segmentation of head and neck tumors plays an important role in radiomics analysis. In this short paper, we propose an automatic segmentation method for head and neck tum…
Histogram Matching Augmentation for Domain Adaptation with Application to Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Image Segmentation
Jun Ma
Convolutional Neural Networks (CNNs) have achieved high accuracy for cardiac structure segmentation if training cases and testing cases are from the same distribution. However, the…
AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?
Jun Ma, Yao Zhang, Song Gu +14
With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved…