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1910.09308
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MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning
21 October 2019
Dominik Muller
Frank Kramer
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Papers citing
"MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning"
7 / 7 papers shown
Title
Medical Image Analysis for Detection, Treatment and Planning of Disease using Artificial Intelligence Approaches
Nand lal Yadav
Satyendra Singh
Rajesh Kumar
Sudhakar Singh
18
0
0
18 May 2024
Large Batch and Patch Size Training for Medical Image Segmentation
Junya Sato
Shoji Kido
19
2
0
24 Oct 2022
Towards a Guideline for Evaluation Metrics in Medical Image Segmentation
Dominik Muller
Iñaki Soto Rey
Frank Kramer
35
277
0
10 Feb 2022
MISeval: a Metric Library for Medical Image Segmentation Evaluation
Dominik Muller
D. Hartmann
Philip Meyer
Florian Auer
Iñaki Soto Rey
Frank Kramer
15
19
0
23 Jan 2022
Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation
Michael Yeung
L. Rundo
Yang Nan
Evis Sala
Carola-Bibiane Schönlieb
Guang Yang
UQCV
19
30
0
31 Oct 2021
Towards Label-Free 3D Segmentation of Optical Coherence Tomography Images of the Optic Nerve Head Using Deep Learning
S. Devalla
T. Pham
S. Panda
Zhang Liang
Giridhar Subramanian
...
L. Schmetterer
S. Perera
Tin Aung
Alexandre Hoang Thiery
M. Girard
20
29
0
22 Feb 2020
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
278
10,608
0
19 Feb 2017
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