B
Bulat Ibragimov
Researcher at University of Copenhagen
Publications - 73
Citations - 2602
Bulat Ibragimov is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Segmentation & Computer science. The author has an hindex of 19, co-authored 55 publications receiving 1687 citations. Previous affiliations of Bulat Ibragimov include Johns Hopkins University & Stanford University.
Papers
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Journal ArticleDOI
Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks
Bulat Ibragimov,Lei Xing +1 more
TL;DR: This work proposed the first deep learning‐based algorithm, for segmentation of OARs in HaN CT images, and compared its performance against state‐of‐the‐art automated segmentation algorithms, commercial software, and interobserver variability.
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A benchmark for comparison of dental radiography analysis algorithms
Ching-Wei Wang,Cheng-Ta Huang,Jia-Hong Lee,Chung-Hsing Li,Sheng-Wei Chang,Ming-Jhih Siao,Tat-Ming Lai,Bulat Ibragimov,Tomaz Vrtovec,Olaf Ronneberger,Philipp Fischer,Timothy F. Cootes,Claudia Lindner +12 more
TL;DR: Based on the quantitative evaluation results, it is believed automatic dental radiography analysis is still a challenging and unsolved problem and the datasets and the evaluation software are made available to the research community, further encouraging future developments in this field.
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Fully automated quantitative cephalometry using convolutional neural networks.
TL;DR: It is demonstrated that CNNs, which merely input raw image patches, are promising for accurate quantitative cephalometry, and high anatomical type classification accuracy for test set is demonstrated.
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Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge
Ching-Wei Wang,Cheng-Ta Huang,Meng-Che Hsieh,Chung-Hsing Li,Sheng-Wei Chang,Wei-Cheng Li,Rémy Vandaele,Raphaël Marée,Sébastien Jodogne,Pierre Geurts,Cheng Chen,Guoyan Zheng,Chengwen Chu,Hengameh Mirzaalian,Ghassan Hamarneh,Tomaz Vrtovec,Bulat Ibragimov +16 more
TL;DR: Evaluation of the methods submitted to the Automatic Cephalometric X-Ray Landmark Detection Challenge provides insights into the performance of different landmark detection approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.
Journal ArticleDOI
Deep neural network ensemble for pneumonia localization from a large-scale chest x-ray database
Ilyas Sirazitdinov,Maksym Kholiavchenko,Tamerlan Mustafaev,Yuan Yixuan,Ramil Kuleev,Bulat Ibragimov +5 more
TL;DR: This work developed a reliable solution for automated pneumonia diagnosis and validated it on the largest clinical database publicity available to date and proposed an ensemble of two convolutional neural networks, namely RetinaNet and Mask R-CNN for pneumonia detection and localization.