Bulat Ibragimov

发表

Segmentation of organs‐at‐risks in head and neck CT images using convolutional neural networks

Bulat Ibragimov, Lei Xing, L. Xing, 2017, Medical physics.

Minimal Variance Sampling in Stochastic Gradient Boosting

Bulat Ibragimov, Gleb Gusev, Gleb Gusev, 2019, NeurIPS.

Automated measurement of anterior and posterior acetabular sector angles

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2012, Medical Imaging.

Accurate landmark-based segmentation by incorporating landmark misdetections

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Segmentation of parotid glands from registered CT and MR images.

Bulat Ibragimov, Lei Xing, Boštjan Likar, 2018, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

RIIS-DenseNet: Rotation-Invariant and Image Similarity Constrained Densely Connected Convolutional Network for Polyp Detection

Bulat Ibragimov, Bin Han, Lei Xing, 2018, MICCAI.

Neural Networks for Deep Radiotherapy Dose Analysis and Prediction of Liver SBRT Outcomes

Bulat Ibragimov, Lei Xing, Albert C. Koong, 2019, IEEE Journal of Biomedical and Health Informatics.

Evaluation of Deep Learning Methods for Bone Suppression from Dual Energy Chest Radiography

Bulat Ibragimov, Ilyas Sirazitdinov, Konstantin Kubrak, 2020, ICANN.

Segmentation of Pathological Structures by Landmark-Assisted Deformable Models

Bulat Ibragimov, Lei Xing, Franjo Pernuš, 2017, IEEE Transactions on Medical Imaging.

Deformable Model-Based Segmentation of Intervertebral Discs from MR Spine Images by Using the SSC Descriptor

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2015, CSI@MICCAI.

Densely Connected Neural Network With Unbalanced Discriminant and Category Sensitive Constraints for Polyp Recognition

Max Q.-H. Meng, Bulat Ibragimov, Lei Xing, 2020, IEEE Transactions on Automation Science and Engineering.

Deep Learning for Diagnosis and Segmentation of Pneumothorax: The Results on the Kaggle Competition and Validation Against Radiologists

Bulat Ibragimov, Ilyas Sirazitdinov, Alexey Tolkachev, 2020, IEEE Journal of Biomedical and Health Informatics.

An Improved Shape-Constrained Deformable Model for Segmentation of Vertebrae from CT Lumbar Spine Images

Bulat Ibragimov, Boštjan Likar, Franjo Pernuš, 2015 .

A Framework for Automated Spine and Vertebrae Interpolation-Based Detection and Model-Based Segmentation

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2015, IEEE Transactions on Medical Imaging.

Interpolation-Based Shape-Constrained Deformable Model Approach for Segmentation of Vertebrae from CT Spine Images

Bulat Ibragimov, Boštjan Likar, Franjo Pernuš, 2015 .

Low dose 4D-CT super-resolution reconstruction via inter-plane motion estimation based on optical flow

Hui Liu, Caiming Zhang, Bulat Ibragimov, 2020, Biomed. Signal Process. Control..

Learning deconvolutional deep neural network for high resolution medical image reconstruction

Jun Xu, Bulat Ibragimov, Lei Xing, 2018, Inf. Sci..

Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

Chengwen Chu, Guoyan Zheng, Ghassan Hamarneh, 2015, IEEE Transactions on Medical Imaging.

Optimal reinforcement of training datasets in semi-supervised landmark-based segmentation

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2015, Medical Imaging.

Data Augmentation for Chest Pathologies Classification

Bulat Ibragimov, Ilyas Sirazitdinov, Maksym Kholiavchenko, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Deep 3D Dose Analysis for Prediction of Outcomes After Liver Stereotactic Body Radiation Therapy

Daniel T. Chang, Bulat Ibragimov, Lei Xing, 2018, MICCAI.

Fully automated quantitative cephalometry using convolutional neural networks

Bulat Ibragimov, Lei Xing, Sercan Ö Arık, 2017, Journal of medical imaging.

Shape Representation for Efficient Landmark-Based Segmentation in 3-D

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2014, IEEE Transactions on Medical Imaging.

A benchmark for comparison of dental radiography analysis algorithms

Timothy F. Cootes, Bulat Ibragimov, Olaf Ronneberger, 2016, Medical Image Anal..

Combining deep learning with anatomical analysis for segmentation of the portal vein for liver SBRT planning

Bulat Ibragimov, Lei Xing, Albert Koong, 2017, Physics in medicine and biology.

Statistical shape representation with landmark clustering by solving the assignment problem

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2013, Medical Imaging.

Kits19 segmentation challenge

Bulat Ibragimov, Ilyas Sirazitdinov, 2019 .

Intervertebral disc segmentation in MR images with 3D convolutional networks

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2017, Medical Imaging.

A multi-center milestone study of clinical vertebral CT segmentation

Ronald M. Summers, Purang Abolmaesumi, Bulat Ibragimov, 2016, Comput. Medical Imaging Graph..

Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation

Jia Gu, Bulat Ibragimov, Lei Xing, 2018, Physics in medicine and biology.

Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge

Hao Chen, Chengwen Chu, Pheng-Ann Heng, 2017, Medical Image Anal..

Boundary detection by linear programming with application to lung fields segmentation

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2011, Medical Imaging.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.

Li Liu, Yong Yin, Bulat Ibragimov, 2017, Physics in medicine and biology.

Auto-segmentation of organs at risk for head and neck radiotherapy planning: from atlas-based to deep learning methods.

Bulat Ibragimov, Franjo Pernuš, Domen Močnik, 2020, Medical physics.

Automated hepatobiliary toxicity prediction after liver stereotactic body radiation therapy with deep learning-based portal vein segmentation

Bulat Ibragimov, Lei Xing, Albert C. Koong, 2020, Neurocomputing.

Deep neural network ensemble for pneumonia localization from a large-scale chest x-ray database

Bulat Ibragimov, Yixuan Yuan, Ilyas Sirazitdinov, 2019, Comput. Electr. Eng..

Prostate cancer classification with multiparametric MRI transfer learning model

Bulat Ibragimov, Lei Xing, Bin Han, 2019, Medical physics.

Manuscript Information Manuscript Files Segmentation of Tongue Muscles from Super-resolution Magnetic Resonance Images Segmentation of Tongue Muscles from Super-resolution Magnetic Resonance Images

Bostjan Likar, Franjo Pernus, Jerry L. Prince, 2022 .

Joint Spatial-Wavelet Dual-Stream Network for Super-Resolution

Bulat Ibragimov, Chen Yang, Yixuan Yuan, 2020, MICCAI.

A Game-Theoretic Framework for Landmark-Based Image Segmentation

Bostjan Likar, Franjo Pernus, Bulat Ibragimov, 2012, IEEE Transactions on Medical Imaging.

Adversarial Reconstruction Loss for Domain Generalization

Bulat Ibragimov, Asad Masood Khattak, Imad Eddine Ibrahim Bekkouch, 2021, IEEE Access.

Mutual-Prototype Adaptation for Cross-Domain Polyp Segmentation

Bulat Ibragimov, Yixuan Yuan, Meilu Zhu, 2021, IEEE Journal of Biomedical and Health Informatics.

Multi-agent shape models for hip landmark detection in MR scans

Bulat Ibragimov, Tomaz Vrtovec, Imad Eddine Ibrahim Bekkouch, 2021, Medical Imaging.

Automatic Cephalometric X-Ray Landmark Detection by Applying Game Theory and Random Forests

Bulat Ibragimov, 2014 .

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

Christina Lioma, Akshay Pai, Bulat Ibragimov, 2020, Scientific Reports.

Computerized Cephalometry by Game Theory with Shape-and Appearance-Based Landmark Refinement

Bulat Ibragimov, Boštjan Likar, Franjo Pernuš, 2016 .

Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT

Bulat Ibragimov, Lei Xing, Albert Koong, 2018, Medical physics.

Landmark-Based Statistical Shape Representations

Bulat Ibragimov, Tomaž Vrtovec, T. Vrtovec, 2017 .