output
20162026
most citedLearning Based Segmentation of CT Brain Images: Application to Post-Operative Hydrocephalic Scans

17 citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing eess.IVShow all

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eess.IV2024★ 3 cited

Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging

Paul Weiser, Georg Langs, Wolfgang Bogner +11

Introduction: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonanc…

eess.IV2017★ 17 cited

Learning Based Segmentation of CT Brain Images: Application to Post-Operative Hydrocephalic Scans

Venkateswararao Cherukuri, Peter Ssenyonga, Benjamin C. Warf +3

Objective: Hydrocephalus is a medical condition in which there is an abnormal accumulation of cerebrospinal fluid (CSF) in the brain. Segmentation of brain imagery into brain tissu…