AIMC Topic: Neoplasm Grading

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ProGleason-GAN: Conditional progressive growing GAN for prostatic cancer Gleason grade patch synthesis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prostate cancer is one of the most common diseases affecting men. The main diagnostic and prognostic reference tool is the Gleason scoring system. An expert pathologist assigns a Gleason grade to a sample of prostate tissue....

Non-invasive grading of brain tumors using online support vector machine with dynamic fuzzy rule-based parameters optimization.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Non-invasive grading of brain tumors provides a valuable understanding of tumor growth that helps choose the proper treatment. In this paper, an online method with an innovative optimization approach as well as a new and fast tumor segmentation metho...

Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning.

European radiology
OBJECTIVES: To establish a robust interpretable multiparametric deep learning (DL) model for automatic noninvasive grading of meningiomas along with segmentation.

A comparative study of the inter-observer variability on Gleason grading against Deep Learning-based approaches for prostate cancer.

Computers in biology and medicine
BACKGROUND: Among all the cancers known today, prostate cancer is one of the most commonly diagnosed in men. With modern advances in medicine, its mortality has been considerably reduced. However, it is still a leading type of cancer in terms of deat...

Investigation of radiomics and deep convolutional neural networks approaches for glioma grading.

Biomedical physics & engineering express
To determine glioma grading by applying radiomic analysis or deep convolutional neural networks (DCNN) and to benchmark both approaches on broader validation sets.Seven public datasets were considered: (1) low-grade glioma or high-grade glioma (369 p...

Incidence and Predicting Factors of Histopathological Features at Robot-Assisted Radical Prostatectomy in the mpMRI Era: Results of a Single Tertiary Referral Center.

Medicina (Kaunas, Lithuania)
: To describe the predictors of cribriform variant status and perineural invasion (PNI) in robot-assisted radical prostatectomy (RARP) histology. To define the rates of upgrading between biopsy specimens and final histology and their possible predict...

Comparison of a machine and deep learning model for automated tumor annotation on digitized whole slide prostate cancer histology.

PloS one
One in eight men will be affected by prostate cancer (PCa) in their lives. While the current clinical standard prognostic marker for PCa is the Gleason score, it is subject to inter-reviewer variability. This study compares two machine learning metho...

Convolutional Neural Network Quantification of Gleason Pattern 4 and Association With Biochemical Recurrence in Intermediate-Grade Prostate Tumors.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Differential classification of prostate cancer grade group (GG) 2 and 3 tumors remains challenging, likely because of the subjective quantification of the percentage of Gleason pattern 4 (%GP4). Artificial intelligence assessment of %GP4 may improve ...