[Retracted] Diagnosis of Prostate Cancer Using GLCM Enabled KNN Technique by Analyzing MRI Images

L Anand, S Mewada, WD Shamsi… - BioMed Research …, 2023 - Wiley Online Library
Cancer has a disproportionately large influence on the death rate of adults. A patient needs
to get a diagnosis of their condition as quickly as is humanly feasible in order to have the …

Computer-aided diagnosis for prostate cancer using multi-parametric magnetic resonance imaging

G Lemaitre - 2016 - u-bourgogne.hal.science
Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. CaP
growth is characterized by two main types of evolution:(i) the slow-growing tumours progress …

Semi-Quantitative Analysis of DCE-MRI for Classification of the Prostate with and without Cancer

H Deng, N Cai, Y Peng - 2021 6th International Conference on …, 2021 - ieeexplore.ieee.org
In our study, we aim to evaluate the diagnostic performance of semi-quantitative parameters
on prostate tumors. Our dataset includes 47 Asian cases with 26 cases showed no signs of …

Machine Learning Approaches for MRI Image Analysis-Based Prostate Cancer Detection

S Mewada, P Sharma - Predicting Pregnancy Complications …, 2023 - igi-global.com
The sooner the patient receives a diagnosis for their condition, the higher their chances will
be of surviving it. As is the case with conventional diagnosis, medical imaging is analyzed by …

10 Computer-Aided Diagnosis

G Lemaître, R Martí, F Meriaudeau - Prostate Cancer Imaging …, 2018 - books.google.com
The prostate is an exocrine gland of the male reproductive system having an inverted
pyramidal shape, which is located below the bladder and in front of the rectum. It measures …

Computer-Aided Diagnosis Systems for Prostate Cancer Detection: Challenges and Methodologies

G Lemaître, R Martí, F Meriaudeau - Prostate Cancer Imaging, 2018 - taylorfrancis.com
Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. CaP
growth is characterized by two main types of evolution:(i) slow-growing tumors progress …