activity
20172021
most citedUniversal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

85 citations · 86 across the 2 of their papers we have counts for

collaborators

5 papers

eess.IV20211 cited

Anatomical and Diagnostic Bayesian Segmentation in Prostate MRI Should Different Clinical Objectives Mandate Different Loss Functions?

Anindo Saha, Joeran Bosma, Jasper Linmans +2

We hypothesize that probabilistic voxel-level classification of anatomy and malignancy in prostate MRI, although typically posed as near-identical segmentation tasks via U-Nets, re…

eess.IV2021

End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction

Anindo Saha, Matin Hosseinzadeh, Henkjan Huisman

We present a multi-stage 3D computer-aided detection and diagnosis (CAD) model for automated localization of clinically significant prostate cancer (csPCa) in bi-parametric MR imag…

eess.IV2020

Encoding Clinical Priori in 3D Convolutional Neural Networks for Prostate Cancer Detection in bpMRI

Anindo Saha, Matin Hosseinzadeh, Henkjan Huisman

We hypothesize that anatomical priors can be viable mediums to infuse domain-specific clinical knowledge into state-of-the-art convolutional neural networks (CNN) based on the U-Ne…

eess.IV2019

Effect of Adding Probabilistic Zonal Prior in Deep Learning-based Prostate Cancer Detection

Matin Hosseinzadeh, Patrick Brand, Henkjan Huisman

We propose and evaluate a novel method for automatically detecting clinically significant prostate cancer (csPCa) in bi-parametric magnetic resonance imaging (bpMRI). Prostate zone…

q-bio.TO201785 cited

Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

Saba Adabi, Matin Hosseinzadeh, Shahryar Noei +5

Currently, diagnosis of skin diseases is based primarily on visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are tr…