Radiomics in renal cell carcinoma—a systematic review and meta-analysis
J Mühlbauer, L Egen, KF Kowalewski, M Grilli… - Cancers, 2021 - mdpi.com
Simple Summary Radiomics may answer questions where the conventional interpretation of
medical imaging has limitations. The aim of our systematic review and meta-analysis was to …
medical imaging has limitations. The aim of our systematic review and meta-analysis was to …
Diagnostic performance of artificial intelligence in detection of renal cell carcinoma: a systematic review and meta-analysis
M Gouravani, M Shahrabi Farahani, MA Salehi… - BMC Cancer, 2025 - Springer
Objectives The detection of renal cell carcinoma (RCC) tumors in the earlier stages is of
great importance for more effective treatment. Encouraged by the key role of imaging in the …
great importance for more effective treatment. Encouraged by the key role of imaging in the …
Ensemble U‐net‐based method for fully automated detection and segmentation of renal masses on computed tomography images
Purpose Detection and accurate localization of renal masses (RM) are important steps
toward future potential classification of benign vs malignant RM. A fully automated algorithm …
toward future potential classification of benign vs malignant RM. A fully automated algorithm …
Deep-learning-based ensemble method for fully automated detection of renal masses on magnetic resonance images
Purpose Accurate detection of small renal masses (SRM) is a fundamental step for
automated classification of benign and malignant or indolent and aggressive renal tumors …
automated classification of benign and malignant or indolent and aggressive renal tumors …
Medical image classification and manifold disease identification through convolutional neural networks: a research perspective
KS Kumar, AS Radhamani, S Sundaresan… - Handbook of Deep …, 2021 - taylorfrancis.com
The medical image classification assumes a basic job in clinical treatment and instructing
aid. The old approach about this medical image classification might have touched its …
aid. The old approach about this medical image classification might have touched its …
Convnext-PCA: A Parameter-Efficient Model for Accurate Kidney Abnormality Classification
This study proposes the integration of principal component analysis (PCA), convolution,
dense residual network (DRN) for the image classification of healthy kidneys, renal cysts …
dense residual network (DRN) for the image classification of healthy kidneys, renal cysts …
Automated Detection of Renal Masses in Contrast-Enhanced MRI using Deep Learning Methods
A Agarwal - 2021 - atrium.lib.uoguelph.ca
Multiparametric MRI based assessment of renal masses in the kidney has the potential to
improve tumour classification accuracy and as a result improve treatment outcomes for renal …
improve tumour classification accuracy and as a result improve treatment outcomes for renal …
Development of Machine Learning Algorithms for Kidney Cancer Diagnosis from Multi-Parametric MRI and Histopathology Images
R Gaikar - 2023 - atrium.lib.uoguelph.ca
Medical imaging techniques like computed tomography (CT), magnetic resonance imaging
(MRI), and histopathology examinations are used to investigate various kidney cancers …
(MRI), and histopathology examinations are used to investigate various kidney cancers …