Publications (5)
Evaluating the Impact of Sequence Combinations on Breast Tumor Segmentation in Multiparametric MRI
Hang Min, Gorane Santamaria Hormaechea, Prabhakar Ramachandran +1
Multiparametric magnetic resonance imaging (mpMRI) is a key tool for assessing breast cancer progression. Although deep learning has been applied to automate tumor segmentation in…
Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN
Hang Min, Devin Wilson, Yinhuang Huang +4
Mammographic mass detection and segmentation are usually performed as serial and separate tasks, with segmentation often only performed on manually confirmed true positive detectio…
Standardized Evaluation of Automatic Methods for Perivascular Spaces Segmentation in MRI -- MICCAI 2024 Challenge Results
Yilei Wu, Yichi Zhang, Zijian Dong +38
Perivascular spaces (PVS), when abnormally enlarged and visible in magnetic resonance imaging (MRI) structural sequences, are important imaging markers of cerebral small vessel dis…
MedNet-PVS: A MedNeXt-Based Deep Learning Model for Automated Segmentation of Perivascular Spaces
Zhen Xuen Brandon Low, Rory Zhang, Hang Min +20
Enlarged perivascular spaces (PVS) are increasingly recognized as biomarkers of cerebral small vessel disease, Alzheimer's disease, stroke, and aging-related neurodegeneration. How…
Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI
Hang Min, Darryl McClymont, Shekhar S. Chandra +2
Previous studies on computer aided detection/diagnosis (CAD) in 4D breast magnetic resonance imaging (MRI) regard lesion detection, segmentation and characterization as separate ta…