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Bogdan J. Matuszewski
Researcher at University of Central Lancashire
Publications - 116
Citations - 2920
Bogdan J. Matuszewski is an academic researcher from University of Central Lancashire. The author has contributed to research in topics: Image segmentation & Segmentation. The author has an hindex of 20, co-authored 110 publications receiving 2268 citations.
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Journal ArticleDOI
Gland segmentation in colon histology images: The GlaS challenge contest
Korsuk Sirinukunwattana,Josien P. W. Pluim,Hao Chen,Xiaojuan Qi,Pheng-Ann Heng,Yun Bo Guo,Li Yang Wang,Bogdan J. Matuszewski,Elia Bruni,Urko Sanchez,Anton Böhm,Olaf Ronneberger,Bassem Ben Cheikh,Daniel Racoceanu,Philipp Kainz,Philipp Kainz,Michael Pfeiffer,Martin Urschler,David Snead,Nasir M. Rajpoot +19 more
TL;DR: An overview to the Gland Segmentation in Colon Histology Images Challenge Contest (GlaS) held at MICCAI'2015 is provided, along with the method descriptions and evaluation results from the top performing methods.
Journal ArticleDOI
Assessment of algorithms for mitosis detection in breast cancer histopathology images
Mitko Veta,Paul J. van Diest,Stefan M. Willems,Haibo Wang,Anant Madabhushi,Angel Cruz-Roa,Fabio A. González,Anders Boesen Lindbo Larsen,Jacob S. Vestergaard,Anders Bjorholm Dahl,Dan Ciresan,Jürgen Schmidhuber,Alessandro Giusti,Luca Maria Gambardella,F. Boray Tek,Thomas Walter,Thomas Walter,Thomas Walter,Ching-Wei Wang,Satoshi Kondo,Satoshi Kondo,Bogdan J. Matuszewski,Frédéric Precioso,Violet Snell,Josef Kittler,Teofilo de Campos,Teofilo de Campos,Adnan Mujahid Khan,Nasir M. Rajpoot,Nasir M. Rajpoot,Evdokia Arkoumani,Miangela M. Lacle,Max A. Viergever,Josien P. W. Pluim +33 more
TL;DR: The results from the Assessment of Mitosis Detection Algorithms 2013 (AMIDA13) challenge are described and the top performing method has an error rate that is comparable to the inter-observer agreement among pathologists.
Journal ArticleDOI
Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge
Jorge Bernal,Nima Tajkbaksh,Francisco Javier Sánchez,Bogdan J. Matuszewski,Hao Chen,Lequan Yu,Quentin Angermann,Olivier Romain,Bjorn Rustad,Ilangko Balasingham,Konstantin Pogorelov,Sungbin Choi,Quentin Debard,Lena Maier-Hein,Stefanie Speidel,Danail Stoyanov,Patrick Brandao,Henry Córdova,Cristina Sánchez-Montes,Suryakanth R. Gurudu,Gloria Fernández-Esparrach,Xavier Dray,Jianming Liang,Aymeric Histace +23 more
TL;DR: Results show that convolutional neural networks are the state of the art in polyp detection and it is also demonstrated that combining different methodologies can lead to an improved overall performance.
Proceedings ArticleDOI
Medical Image Segmentation Using New Hybrid Level-Set Method
TL;DR: A new hybrid medical image segmentation method in the level-set framework that uses both the objectpsilas boundary and region information to achieve robust and accurate segmentation results is proposed.
Journal ArticleDOI
Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography.
Hortense A. Kirisli,Michiel Schaap,Coert Metz,Anoeshka S. Dharampal,Willem B. Meijboom,Stella-Lida Papadopoulou,Admir Dedic,Koen Nieman,M. A. de Graaf,M. F. L. Meijs,M. J. Cramer,A. Broersen,Suheyla Cetin,Abouzar Eslami,Leonardo Flórez-Valencia,K.L. Lor,Bogdan J. Matuszewski,I. Melki,I. Melki,B. Mohr,Ilkay Oksuz,Rahil Shahzad,Rahil Shahzad,Chunliang Wang,Pieter H. Kitslaar,Gozde Unal,Amin Katouzian,Amin Katouzian,Maciej Orkisz,Chung-Ming Chen,Frédéric Precioso,Laurent Najman,S. Masood,Devrim Unay,L.J. van Vliet,Rodrigo Moreno,Roman Goldenberg,E. Vuçini,Gabriel P. Krestin,Wiro J. Niessen,Wiro J. Niessen,T. van Walsum +41 more
TL;DR: Results show that some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that automatic lumen segmentation is possible with a precision similar to that obtained by experts.