Objective task-based evaluation of artificial intelligence-based medical imaging methods: framework, strategies, and role of the physician

AK Jha, KJ Myers, NA Obuchowski, Z Liu… - PET clinics, 2021 - pet.theclinics.com
Artificial intelligence (AI)-based methods for medical imaging, and more specifically PET,
hold exciting promise in multiple stages of the imaging–technology–development lifecycle …

Toward high-throughput artificial intelligence-based segmentation in oncological PET imaging

F Yousefirizi, AK Jha, J Brosch-Lenz, B Saboury… - PET clinics, 2021 - pet.theclinics.com
An array of artificial intelligence (AI) techniques in the field of medical imaging has emerged
in the past decade for automated image segmentation. 1 Medical image segmentation seeks …

Right ventricle segmentation from cardiac MRI: a collation study

C Petitjean, MA Zuluaga, W Bai, JN Dacher… - Medical image …, 2015 - Elsevier
Abstract Magnetic Resonance Imaging (MRI), a reference examination for cardiac
morphology and function in humans, allows to image the cardiac right ventricle (RV) with …

A novel U-Net approach to segment the cardiac chamber in magnetic resonance images with ghost artifacts

M Zhao, Y Wei, Y Lu, KKL Wong - Computer Methods and Programs in …, 2020 - Elsevier
Objective We propose a robust technique for segmenting magnetic resonance images of
post-atrial septal occlusion intervention in the cardiac chamber. Methods A variant of the U …

Comparative analysis of active contour and convolutional neural network in rapid left-ventricle volume quantification using echocardiographic imaging

X Zhu, Y Wei, Y Lu, M Zhao, K Yang, S Wu… - Computer Methods and …, 2021 - Elsevier
In cardiology, ultrasound is often used to diagnose heart disease associated with myocardial
infarction. This study aims to develop robust segmentation techniques for segmenting the left …

An improved FSL-FIRST pipeline for subcortical gray matter segmentation to study abnormal brain anatomy using quantitative susceptibility mapping (QSM)

X Feng, A Deistung, MG Dwyer, J Hagemeier… - Magnetic Resonance …, 2017 - Elsevier
Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in
many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool …

A graph-based mathematical morphology reader

L Najman, J Cousty - Pattern Recognition Letters, 2014 - Elsevier
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A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods

AK Jha, B Caffo, EC Frey - Physics in Medicine & Biology, 2016 - iopscience.iop.org
The objective optimization and evaluation of nuclear-medicine quantitative imaging methods
using patient data is highly desirable but often hindered by the lack of a gold standard …

Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography

AK Jha, E Mena, B Caffo, S Ashrafinia… - Journal of Medical …, 2017 - spiedigitallibrary.org
Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate
quantitative imaging methods using patient data. These techniques provide figures of merit …

Fully automated segmentation of the left ventricle applied to cine mr images: description and results on a database of 45 subjects

C Constantinidès, E Roullot, M Lefort… - … Conference of the …, 2012 - ieeexplore.ieee.org
A fully automated segmentation method of the left ventricle from short-axis cardiac MR
images is proposed and evaluated. The segmentation is based on morphological filtering …