Alfiia Galimzianova

According to our database, Alfiia Galimzianova authored at least 14 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

DermX: An end-to-end framework for explainable automated dermatological diagnosis.

Raluca Jalaboi, Frederik Faye, Mauricio Orbes-Arteaga, Dan Richter Jørgensen, Ole Winther, Alfiia Galimzianova

Medical Image Anal., 2023

Dermatological Diagnosis Explainability Benchmark for Convolutional Neural Networks.

Raluca Jalaboi, Ole Winther, Alfiia Galimzianova

CoRR, 2023

2022

Explainable Image Quality Assessments in Teledermatological Photography.

Raluca Jalaboi, Ole Winther, Alfiia Galimzianova

CoRR, 2022

2018

A Novel Public MR Image Dataset of Multiple Sclerosis Patients With Lesion Segmentations Based on Multi-rater Consensus.

Ziga Lesjak, Alfiia Galimzianova, Ales Koren, Matej Lukin, Franjo Pernus, Bostjan Likar, Ziga Spiclin

Neuroinformatics, 2018

A Multi-scale Multiple Sclerosis Lesion Change Detection in a Multi-sequence MRI.

Myra Cheng, Alfiia Galimzianova, Ziga Lesjak, Ziga Spiclin, Christopher B. Lock, Daniel L. Rubin

Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018

2017

A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound.

Karim Lekadir, Alfiia Galimzianova, Àngels Betriu, Maria del Mar Vila, Laura Igual, Daniel L. Rubin, Elvira Fernández, Petia Radeva, Sandy Napel

IEEE J. Biomed. Health Informatics, 2017

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Zeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, Daniel L. Rubin, Bradley J. Erickson

J. Digit. Imaging, 2017

Toward Automated Pre-Biopsy Thyroid Cancer Risk Estimation in Ultrasound.

Alfiia Galimzianova, Sean M. Siebert, Aya Kamaya, Terry S. Desser, Daniel L. Rubin

Proceedings of the AMIA 2017, 2017

2016

Stratified mixture modeling for segmentation of white-matter lesions in brain MR images.

Alfiia Galimzianova, Franjo Pernus, Bostjan Likar, Ziga Spiclin

NeuroImage, 2016

2015

Robust Estimation of Unbalanced Mixture Models on Samples with Outliers.

Alfiia Galimzianova, Franjo Pernus, Bostjan Likar, Ziga Spiclin

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions.

Alfiia Galimzianova, Ziga Lesjak, Bostjan Likar, Franjo Pernus, Ziga Spiclin

Proceedings of the Medical Imaging 2015: Image Processing, 2015

Combining Unsupervised and Supervised Methods for Lesion Segmentation.

Tim Jerman, Alfiia Galimzianova, Franjo Pernus, Bostjan Likar, Ziga Spiclin

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015

2013

Automated segmentation of MS lesions in brain MR images using localized trimmed-likelihood estimation.

Alfiia Galimzianova, Ziga Spiclin, Bostjan Likar, Franjo Pernus

Proceedings of the Medical Imaging 2013: Image Processing, 2013

Robust Mixture-Parameter Estimation for Unsupervised Segmentation of Brain MR Images.

Alfiia Galimzianova, Ziga Spiclin, Bostjan Likar, Franjo Pernus

Proceedings of the Medical Computer Vision. Large Data in Medical Imaging, 2013