Human activity recognition in artificial intelligence framework: a narrative review

N Gupta, SK Gupta, RK Pathak, V Jain… - Artificial intelligence …, 2022 - Springer
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …

An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review

S Das, GK Nayak, L Saba, M Kalra, JS Suri… - Computers in biology and …, 2022 - Elsevier
Background Artificial intelligence (AI) has become a prominent technique for medical
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …

Methods for nuclei detection, segmentation, and classification in digital histopathology: a review—current status and future potential

H Irshad, A Veillard, L Roux… - IEEE reviews in …, 2013 - ieeexplore.ieee.org
Digital pathology represents one of the major evolutions in modern medicine. Pathological
examinations constitute the gold standard in many medical protocols, and also play a critical …

Development of a new generation of high-resolution anatomical models for medical device evaluation: the Virtual Population 3.0

MC Gosselin, E Neufeld, H Moser… - Physics in Medicine …, 2014 - iopscience.iop.org
Abstract The Virtual Family computational whole-body anatomical human models were
originally developed for electromagnetic (EM) exposure evaluations, in particular to study …

The Virtual Family—development of surface-based anatomical models of two adults and two children for dosimetric simulations

A Christ, W Kainz, EG Hahn, K Honegger… - Physics in Medicine …, 2009 - iopscience.iop.org
The objective of this study was to develop anatomically correct whole body human models of
an adult male (34 years old), an adult female (26 years old) and two children (an 11-year-old …

[HTML][HTML] State-of-the-art review on deep learning in medical imaging

M Biswas, V Kuppili, L Saba, DR Edla… - Frontiers in Bioscience …, 2019 - imrpress.com
Deep learning (DL) is affecting each and every sphere of public and private lives and
becoming a tool for daily use. The power of DL lies in the fact that it tries to imitate the …

Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A …

M Agarwal, S Agarwal, L Saba, GL Chabert… - Computers in biology …, 2022 - Elsevier
Abstract Background COVLIAS 1.0: an automated lung segmentation was designed for
COVID-19 diagnosis. It has issues related to storage space and speed. This study shows …

Deformable models in medical image analysis: a survey

T McInerney, D Terzopoulos - Medical image analysis, 1996 - Elsevier
This article surveys deformable models, a promising and vigorously researched computer-
assisted medical image analysis technique. Among model-based techniques, deformable …

Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation

BN Li, CK Chui, S Chang, SH Ong - Computers in biology and medicine, 2011 - Elsevier
The performance of the level set segmentation is subject to appropriate initialization and
optimal configuration of controlling parameters, which require substantial manual …

Recommended implementation of quantitative susceptibility map** for clinical research in the brain: a consensus of the ISMRM electro‐magnetic tissue properties …

QSM Consensus Organization … - Magnetic resonance …, 2024 - Wiley Online Library
This article provides recommendations for implementing QSM for clinical brain research. It is
a consensus of the International Society of Magnetic Resonance in Medicine, Electro …