activity
20182022
most citedAnatomical and Diagnostic Bayesian Segmentation in Prostate MRI Should Different Clinical Objectives Mandate Different Loss Functions?

1 citations · 1 across the 3 of their papers we have counts for

collaborators

8 papers

eess.IV2022

Few-shot image segmentation for cross-institution male pelvic organs using registration-assisted prototypical learning

Yiwen Li, Yunguan Fu, Qianye Yang +6

The ability to adapt medical image segmentation networks for a novel class such as an unseen anatomical or pathological structure, when only a few labelled examples of this class a…

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

Cine-MRI detection of abdominal adhesions with spatio-temporal deep learning

Bram de Wilde, Richard P. G. ten Broek, Henkjan Huisman

Adhesions are an important cause of chronic pain following abdominal surgery. Recent developments in abdominal cine-MRI have enabled the non-invasive diagnosis of adhesions. Adhesi…

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…