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Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging
Vishnu M. Bashyam, Jimit Doshi, Guray Erus +24
Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and…
A Deep Network for Joint Registration and Reconstruction of Images with Pathologies
Xu Han, Zhengyang Shen, Zhenlin Xu +5
Registration of images with pathologies is challenging due to tissue appearance changes and missing correspondences caused by the pathologies. Moreover, mass effects as observed fo…
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos +6
Since its renaissance, deep learning has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propell…
MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases
Junhao Wen, Erdem Varol, Ganesh Chand +2
There is a growing amount of clinical, anatomical and functional evidence for the heterogeneous presentation of neuropsychiatric and neurodegenerative diseases such as schizophreni…
Smile-GANs: Semi-supervised clustering via GANs for dissecting brain disease heterogeneity from medical images
Zhijian Yang, Junhao Wen, Christos Davatzikos
Machine learning methods applied to complex biomedical data has enabled the construction of disease signatures of diagnostic/prognostic value. However, less attention has been give…
Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology
Andreas Mang, Spyridon Bakas, Shashank Subramanian +2
Central nervous system (CNS) tumors come with the vastly heterogeneous histologic, molecular and radiographic landscape, rendering their precise characterization challenging. The r…