Matin Hosseinzadeh

I am a PhD candidate at the Diagnostic Image Analysis Group (DIAG), Radboudumc. I'm working under supervision of Henkjan Huisman and supported by Siemens Healthineers.

In 2017 I graduated with an M.Sc. in Biomedical Engineering from Sharif University of Technology, where I did research on human action recognition from depth videos at the Biomedical Signal and Image Processing Laboratory. Before that, I recieved my B.Sc. degree in Electrical Engineering from Semnan University in 2012.

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prl
Research

My interests are broadly in machine learning, deep learning and computer vision. I have worked on problems in the domains of 2D and 3D object detection, semantic segmentation, generative models and image classification. For my PhD project, I study deep learning methods for 3D medical image analysis with specific application for prostate cancer detection in mpMRI.






Publications
For an updated list of publications, please visit my Google Scholar page.
prl Uncertainty-Aware Semi-Supervised Learning for Prostate MRI Zonal Segmentation
Matin Hosseinzadeh, Anindo Saha, Joeran Bosma, Henkjan Huisman
Arxiv / Code

prl Semisupervised learning with report-guided pseudo labels for deep learning–based prostate cancer detection using biparametric MRI
Joeran S. Bosma, Anindo Saha, Matin Hosseinzadeh, Ilse Slootweg, Maarten de Rooij, and Henkjan Huisman
Radiology: Artificial Intelligence, 2023
Paper / Code / Demo

prl Deep Learning assisted Prostate Cancer Detection on Bi-parametric MRI: Minimum Training Data Size Requirements and Effect of Prior Knowledge
Matin Hosseinzadeh, Anindo Saha, Patrick Brand, Ilse Slootweg, Maarten de Rooij, Henkjan Huisman
European Radiology 2021
Paper

prl Anatomical and Diagnostic Bayesian Segmentation in Prostate MRI –Should Different Clinical Objectives Mandate Different Loss Functions?
Anindo Saha, Joeran Bosma, Jasper Linmans, Matin Hosseinzadeh, Henkjan Huisman
Medical Imaging Meets NeurIPS Workshop 2021
Paper / Code

prl End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effect of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction
Anindo Saha✝, Matin Hosseinzadeh✝, Henkjan Huisman (✝ equal contribution)
Medical Image Analysis 2021
Paper / Code / Demo

prl Multi-Modal Siamese Network for Diagnostically Similar Lesion Retrieval in Prostate MRI
Alberto Rossi, Matin Hosseinzadeh, Monica Bianchini, Franco Scarselli, Henkjan Huisman
IEEE Transactions on Medical Imaging 2020
Paper / Code

prl Encoding Clinical Priori in 3D Convolutional Neural Networks for Prostate Cancer Detection in bpMRI
Anindo Saha, Matin Hosseinzadeh, Henkjan Huisman
Medical Imaging Meets NeurIPS Workshop 2020
Paper / Code

prl Anisotropic Deep Learning Multi-planar Automatic Prostate Segmentation
Tabea Riepe, Matin Hosseinzadeh, Patrick Brand, and Henkjan Huisman
International Society for Magnetic Resonance in Medicine (ISMRM 2020)
Paper

prl Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI
Coen De Vente, Pieter Vos, Matin Hosseinzadeh, Josien Pluim, Mitko Veta
IEEE Transactions on Biomedical Engineering 2020
Paper

prl Effect of Adding Probabilistic Zonal Prior in Deep Learning-based Prostate Cancer Detection
Matin Hosseinzadeh, Patrick Brand, Henkjan Huisman
International Conference on Medical Imaging with Deep Learning (MIDL 2019)
Paper

prl Photoacoustic Signal Enhancement: Towards Utilization of Low Energy Laser Diodes in Real-Time Photoacoustic Imaging
Rayyan Manwar, Matin Hosseinzadeh, Ali Hariri, Karl Kratkiewicz, Shahryar Noei, Mohammad R N Avanaki
Sensors 2018
Paper

prl Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms
Saba Adabi, Matin Hosseinzadeh, Shahryar Noei, Steven Daveluy, Anne Clayton, Darius Mehregan, Silvia Conforto, Mohammadreza Nasiriavanaki
Scientific Reports 2017
Paper


Credits to Jon for this template.