# Bulat Ibragimov

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/bulat-ibragimov/

## Facts

| Field | Value |
| --- | --- |
| Citations | 4,244 |
| Field | Radiomics and Machine Learning in Medical Imaging |
| h-index | 31 |
| i10-index | 54 |
| Last Known Institution | University of Copenhagen |
| OpenAlex ID | https://openalex.org/A5070871008 |
| ORCID iD | 0000-0001-7739-7788 |
| Works | 137 |

## Researcher papers

- [Segmentation of organs‐at‐risks in head and neck <scp>CT</scp> images using convolutional neural networks](https://scholariq.org/papers/segmentation-of-organs-at-risks-in-head-and-neck-scp-ct-scp-images-using/)
- [A benchmark for comparison of dental radiography analysis algorithms](https://scholariq.org/papers/a-benchmark-for-comparison-of-dental-radiography-analysis-algorithms/)
- [Fully automated quantitative cephalometry using convolutional neural networks](https://scholariq.org/papers/fully-automated-quantitative-cephalometry-using-convolutional-neural-networks/)
- [Deep neural network ensemble for pneumonia localization from a large-scale chest x-ray database](https://scholariq.org/papers/deep-neural-network-ensemble-for-pneumonia-localization-from-a-large-scale-chest/)
- [Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge](https://scholariq.org/papers/evaluation-and-comparison-of-anatomical-landmark-detection-methods-for/)
- [Auto‐segmentation of organs at risk for head and neck radiotherapy planning: From atlas‐based to deep learning methods](https://scholariq.org/papers/auto-segmentation-of-organs-at-risk-for-head-and-neck-radiotherapy-planning-from/)
- [A multi-center milestone study of clinical vertebral CT segmentation](https://scholariq.org/papers/a-multi-center-milestone-study-of-clinical-vertebral-ct-segmentation/)
- [Prostate cancer classification with multiparametric MRI transfer learning model](https://scholariq.org/papers/prostate-cancer-classification-with-multiparametric-mri-transfer-learning-model/)
- [A Framework for Automated Spine and Vertebrae Interpolation-Based Detection and Model-Based Segmentation](https://scholariq.org/papers/a-framework-for-automated-spine-and-vertebrae-interpolation-based-detection-and/)
- [Development of deep neural network for individualized hepatobiliary toxicity prediction after liver <scp>SBRT</scp>](https://scholariq.org/papers/development-of-deep-neural-network-for-individualized-hepatobiliary-toxicity/)
- [Deep Learning for Detection of Clinical Operations in Robot-Assisted Percutaneous Renal Access](https://scholariq.org/papers/deep-learning-for-detection-of-clinical-operations-in-robot-assisted/)

## Researcher topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Medical Imaging and Analysis](https://scholariq.org/topics/medical-imaging-and-analysis/)
- [Dental Radiography and Imaging](https://scholariq.org/topics/dental-radiography-and-imaging/)
- [Advanced Radiotherapy Techniques](https://scholariq.org/topics/advanced-radiotherapy-techniques/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

## Researcher university

- [University of Copenhagen](https://scholariq.org/institutions/university-of-copenhagen/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.