162 citations · 317 across the 7 of their papers we have counts for
7 papers
Uncertainty-Aware Semi-Supervised Learning for Prostate MRI Zonal Segmentation
Matin Hosseinzadeh, Anindo Saha, Joeran Bosma +1
Quality of deep convolutional neural network predictions strongly depends on the size of the training dataset and the quality of the annotations. Creating annotations, especially f…
Annotation-efficient cancer detection with report-guided lesion annotation for deep learning-based prostate cancer detection in bpMRI
Joeran S. Bosma, Anindo Saha, Matin Hosseinzadeh +3
Deep learning-based diagnostic performance increases with more annotated data, but large-scale manual annotations are expensive and labour-intensive. Experts evaluate diagnostic im…
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…
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…
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…
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…
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…