Advances in diagnosis and therapy for bladder cancer

X Hu, G Li, S Wu - Cancers, 2022 - mdpi.com
Simple Summary The clinical management of bladder cancer has been developing in the
past decade, including diagnostic tools and treatment options. Both monotherapy and …

MRI-based radiomics in bladder cancer: a systematic review and radiomics quality score assessment

B Boca, C Caraiani, T Telecan, R Pintican, A Lebovici… - Diagnostics, 2023 - mdpi.com
(1): Background: With the recent introduction of vesical imaging reporting and data system
(VI-RADS), magnetic resonance imaging (MRI) has become the main imaging method used …

Performing automatic identification and staging of urothelial carcinoma in bladder cancer patients using a hybrid deep-machine learning approach

S Sarkar, K Min, W Ikram, RW Tatton, IB Riaz, AC Silva… - Cancers, 2023 - mdpi.com
Simple Summary Early and accurate bladder cancer staging is important as it determines
the mode of initial treatment. Non-muscle invasive bladder cancer (NMIBC) can be treated …

Predicting muscle invasion in bladder cancer based on MRI: A comparison of radiomics, and single-task and multi-task deep learning

J Li, Z Qiu, K Cao, L Deng, W Zhang, C Xie… - Computer Methods and …, 2023 - Elsevier
Background and objectives Radiomics and deep learning are two popular technologies
used to develop computer-aided detection and diagnosis schemes for analysing medical …

A deep learning pipeline for grade groups classification using digitized prostate biopsy specimens

K Hammouda, F Khalifa, M El-Melegy, M Ghazal… - Sensors, 2021 - mdpi.com
Prostate cancer is a significant cause of morbidity and mortality in the USA. In this paper, we
develop a computer-aided diagnostic (CAD) system for automated grade groups (GG) …

Study of the Current Trends of CAD (Computer-Aided Detection) in Modern Medical Imaging

R Barua, J Mondal - Machine Learning and AI Techniques in …, 2023 - igi-global.com
CAD or computer-aided detection is a valuable performance for exactly understanding
medical images. Also, it has a worldwide business prospect. The present features …

The role of radiomics with machine learning in the prediction of muscle-invasive bladder cancer: a mini review

X Huang, X Wang, X Lan, J Deng, Y Lei, F Lin - Frontiers in Oncology, 2022 - frontiersin.org
Bladder cancer is a common malignant tumor in the urinary system. Depending on whether
bladder cancer invades muscle tissue, it is classified into non-muscle-invasive bladder …

A machine learning model based on MRI for the preoperative prediction of bladder cancer invasion depth

G Chen, X Fan, T Wang, E Zhang, J Shao, S Chen… - European …, 2023 - Springer
Objectives To construct and validate a prediction model based on full-sequence MRI for
preoperatively evaluating the invasion depth of bladder cancer. Methods A total of 445 …

A brief review of artificial intelligence in genitourinary oncological imaging

EC Yilmaz, MJ Belue, B Turkbey… - Canadian …, 2023 - journals.sagepub.com
Genitourinary (GU) system is among the most commonly involved malignancy sites in the
human body. Imaging plays a crucial role not only in diagnosis of cancer but also in disease …

Multi-stage classification-based deep learning for gleason system grading using histopathological images

K Hammouda, F Khalifa, NS Alghamdi, H Darwish… - Cancers, 2022 - mdpi.com
Simple Summary Prostate cancer (PC) is the most common cancer and the second that
causes death in the US. The means of PC treatment have improved with the low-risk disease …