Kaisar Kushibar

Orcid: 0000-0001-7507-5208

According to our database1, Kaisar Kushibar authored at least 21 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Debiasing Cardiac Imaging with Controlled Latent Diffusion Models.
CoRR, 2024

Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models.
CoRR, 2024

2023
Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.
IEEE J. Biomed. Health Informatics, July, 2023

Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging.
Medical Image Anal., 2023

Revisiting Skin Tone Fairness in Dermatological Lesion Classification.
Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023

2022
medigan: A Python Library of Pretrained Generative Models for Enriched Data Access in Medical Imaging.
CoRR, 2022

High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection.
CoRR, 2022

Sharing Generative Models Instead of Private Data: A Simulation Study on Mammography Patch Classification.
CoRR, 2022

Domain generalization in deep learning based mass detection in mammography: A large-scale multi-center study.
Artif. Intell. Medicine, 2022

Layer Ensembles: A Single-Pass Uncertainty Estimation in Deep Learning for Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021
Generating Longitudinal Atrophy Evaluation Datasets on Brain Magnetic Resonance Images Using Convolutional Neural Networks and Segmentation Priors.
Neuroinformatics, 2021

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging.
CoRR, 2021

A Review of Generative Adversarial Networks in Cancer Imaging: New Applications, New Solutions.
CoRR, 2021

Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease.
CoRR, 2021

Center Dropout: A Simple Method for Speed and Fairness in Federated Learning.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2020
Automatic segmentation of brain structures in magnetic resonance images using deep learning techniques.
PhD thesis, 2020

2019
A Hybrid SLAM and Object Recognition System for Pepper Robot.
CoRR, 2019

Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review.
Artif. Intell. Medicine, 2019

Quantitative Analysis of Patch-Based Fully Convolutional Neural Networks for Tissue Segmentation on Brain Magnetic Resonance Imaging.
IEEE Access, 2019

2018
Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features.
Medical Image Anal., 2018

Survival prediction using ensemble tumor segmentation and transfer learning.
CoRR, 2018


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