Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging
M Arabahmadi, R Farahbakhsh, J Rezazadeh - Sensors, 2022 - mdpi.com
Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …
use of technology in medicine has made significant contributions to human society. In this …
[HTML][HTML] An overview of deep learning in medical imaging focusing on MRI
AS Lundervold, A Lundervold - Zeitschrift für Medizinische Physik, 2019 - Elsevier
What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
medical image analysis? Machine learning has witnessed a tremendous amount of attention …
Classification of cancer at prostate MRI: deep learning versus clinical PI-RADS assessment
Background Men suspected of having clinically significant prostate cancer (sPC)
increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic …
increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic …
The present and future of deep learning in radiology
Abstract The advent of Deep Learning (DL) is poised to dramatically change the delivery of
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …
A review of explainable deep learning cancer detection models in medical imaging
Deep learning has demonstrated remarkable accuracy analyzing images for cancer
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …
ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans
Multiparametric magnetic resonance imaging (mp-MRI) has shown excellent results in the
detection of prostate cancer (PCa). However, characterizing prostate lesions …
detection of prostate cancer (PCa). However, characterizing prostate lesions …
Artificial intelligence and machine learning in prostate cancer patient management—current trends and future perspectives
OS Tătaru, MD Vartolomei, JJ Rassweiler, O Virgil… - Diagnostics, 2021 - mdpi.com
Artificial intelligence (AI) is the field of computer science that aims to build smart devices
performing tasks that currently require human intelligence. Through machine learning (ML) …
performing tasks that currently require human intelligence. Through machine learning (ML) …
[HTML][HTML] Convolutional neural networks for computer-aided detection or diagnosis in medical image analysis: An overview
J Gao, Q Jiang, B Zhou, D Chen - Mathematical Biosciences and …, 2019 - aimspress.com
Computer-aided detection or diagnosis (CAD) has been a promising area of research over
the last two decades. Medical image analysis aims to provide a more efficient diagnostic and …
the last two decades. Medical image analysis aims to provide a more efficient diagnostic and …
An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of …
Summary Background Biparametric MRI (comprising T2-weighted MRI and apparent
diffusion coefficient maps) is increasingly being used to characterise prostate cancer …
diffusion coefficient maps) is increasingly being used to characterise prostate cancer …
Joint prostate cancer detection and Gleason score prediction in mp-MRI via FocalNet
Multi-parametric MRI (mp-MRI) is considered the best non-invasive imaging modality for
diagnosing prostate cancer (PCa). However, mp-MRI for PCa diagnosis is currently limited …
diagnosing prostate cancer (PCa). However, mp-MRI for PCa diagnosis is currently limited …