AIMC Topic: Adenoma, Oxyphilic

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Using deep learning to differentiate among histology renal tumor types in computed tomography scans.

BMC medical imaging Feb 26, 2025
BACKGROUND: This study employed a convolutional neural network (CNN) to analyze computed tomography (CT) scans with the aim of differentiating among renal tumors according to histologic sub-type.
Female Aged Adult Male Humans Neural Networks, Computer Kidney Neoplasms Tomography, X-Ray Computed Carcinoma, Renal Cell Angiomyolipoma Adenoma, Oxyphilic Middle Aged Deep Learning Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted
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Deep learning-based diagnosis and survival prediction of patients with renal cell carcinoma from primary whole slide images.

Pathology Aug 3, 2024
There is an urgent clinical demand to explore novel diagnostic and prognostic biomarkers for renal cell carcinoma (RCC). We proposed deep learning-based artificial intelligence strategies. The study included 1752 whole slide images from multiple cent...
Male Female Middle Aged Diagnosis, Differential Humans Aged Deep Learning Prognosis Kidney Neoplasms Adult ROC Curve Carcinoma, Renal Cell Biomarkers, Tumor Adenoma, Oxyphilic
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Oncocytic adrenocortical neoplasm of borderline uncertain malignant potential diagnosed after robot-assisted adrenalectomy case report.

BMC urology Apr 15, 2023
BACKGROUND: Adrenal incidentalomas are radiologically discovered tumors that represent a variety of pathologies, with the diagnosis clinched only on surgical pathology. These tumors may be clinically monitored, but triggers for surgery include size >...
Adrenal Gland Neoplasms Robotics Adrenalectomy Incidental Findings Humans Aged Male Adenoma, Oxyphilic
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Oncocytoma-Related Gene Signature to Differentiate Chromophobe Renal Cancer and Oncocytoma Using Machine Learning.

Cells Jan 15, 2022
Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discover...
Carcinoma, Renal Cell Carbohydrate Metabolism Genes, Neoplasm Adenoma, Oxyphilic Gene Expression Regulation, Neoplastic Databases, Genetic Diagnosis, Differential Warburg Effect, Oncologic Humans Machine Learning Algorithms Reproducibility of Results Gene Expression Profiling ROC Curve
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A deep-learning based artificial intelligence (AI) approach for differentiation of clear cell renal cell carcinoma from oncocytoma on multi-phasic MRI.

Clinical imaging Jun 18, 2021
PURPOSE: To investigate the diagnostic performance of a deep convolutional neural network for differentiation of clear cell renal cell carcinoma (ccRCC) from renal oncocytoma.
Adenoma, Oxyphilic Diagnosis, Differential Cell Differentiation Kidney Neoplasms Carcinoma, Renal Cell Middle Aged Deep Learning Magnetic Resonance Imaging Humans Artificial Intelligence Retrospective Studies Male
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Deep learning based classification of solid lipid-poor contrast enhancing renal masses using contrast enhanced CT.

The British journal of radiology May 11, 2020
OBJECTIVE: Establish a workflow that utilizes convolutional neural nets (CNN) to classify solid, lipid-poor, contrast enhancing renal masses using multiphase contrast enhanced CT (CECT) images and to assess the performance of the resulting network.
Humans Kidney Neoplasms Carcinoma, Renal Cell Angiomyolipoma Male Retrospective Studies Adenoma, Oxyphilic Middle Aged Tomography, X-Ray Computed Deep Learning Female Contrast Media
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Automated classification of solid renal masses on contrast-enhanced computed tomography images using convolutional neural network with decision fusion.

European radiology Apr 29, 2020
OBJECTIVES: To develop a deep learning-based method for automated classification of renal cell carcinoma (RCC) from benign solid renal masses using contrast-enhanced computed tomography (CECT) images.
Contrast Media Diagnosis, Differential Image Interpretation, Computer-Assisted Kidney Neoplasms Machine Learning Humans Carcinoma, Renal Cell Neural Networks, Computer Algorithms Angiomyolipoma Retrospective Studies Adenoma, Oxyphilic Tomography, X-Ray Computed
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Automated differentiation of benign renal oncocytoma and chromophobe renal cell carcinoma on computed tomography using deep learning.

BJU international Feb 6, 2020
OBJECTIVES: To develop and evaluate the feasibility of an objective method using artificial intelligence (AI) and image processing in a semi-automated fashion for tumour-to-cortex peak early-phase enhancement ratio (PEER) in order to differentiate CD...
Adenoma, Oxyphilic Humans Diagnosis, Differential Feasibility Studies Kidney Neoplasms Carcinoma, Renal Cell Retrospective Studies Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted
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Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT.

Abdominal radiology (New York) Jun 1, 2019
PURPOSE: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cel...
Multidetector Computed Tomography Carcinoma, Renal Cell Adenoma, Oxyphilic Radiographic Image Interpretation, Computer-Assisted Kidney Neoplasms Iohexol Adult Sensitivity and Specificity Male Middle Aged Humans Retrospective Studies Deep Learning Software Contrast Media Female Algorithms Diagnosis, Differential Aged Aged, 80 and over
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