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T. Fechter

3 papers here

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author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV1

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedConvolutional neural network based deep-learning architecture for intraprostatic tumour contouring on PSMA PET images in patients with primary prostate cancer

4 citations · 4 across the 2 of their papers we have counts for

collaborators

3 papers

eess.IV2022

IB-U-Nets: Improving medical image segmentation tasks with 3D Inductive Biased kernels

Shrajan Bhandary, Zahra Babaiee, Dejan Kostyszyn +4

Despite the success of convolutional neural networks for 3D medical-image segmentation, the architectures currently used are still not robust enough to the protocols of different s…

cs.CV2020★ 4 cited

Convolutional neural network based deep-learning architecture for intraprostatic tumour contouring on PSMA PET images in patients with primary prostate cancer

Dejan Kostyszyn, Tobias Fechter, Nico Bartl +22

Accurate delineation of the intraprostatic gross tumour volume (GTV) is a prerequisite for treatment approaches in patients with primary prostate cancer (PCa). Prostate-specific me…

cs.CV2019

One Shot Learning for Deformable Medical Image Registration and Periodic Motion Tracking

Tobias Fechter, Dimos Baltas

Deformable image registration is a very important field of research in medical imaging. Recently multiple deep learning approaches were published in this area showing promising res…

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