AIMC Topic: Precancerous Conditions
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Two dimensional multifractal detrended fluctuation analysis of low coherence images for diagnosis of cervical pre-cancer.
Biomedical physics & engineering express
Feb 18, 2020
We report detection of cervical pre-cancer through their low coherence images by applying two dimensional multifractal detrended fluctuation analysis. Low coherent backscattered images of pre-cancerous cervical tissue sections were captured using a c...
Deep principal dimension encoding for the classification of early neoplasia in Barrett's Esophagus with volumetric laser endomicroscopy.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 24, 2020
Barrett cancer is a treatable disease when detected at an early stage. However, current screening protocols are often not effective at finding the disease early. Volumetric Laser Endomicroscopy (VLE) is a promising new imaging tool for finding dyspla...
A personalized computational model predicts cancer risk level of oral potentially malignant disorders and its web application for promotion of non-invasive screening.
Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
Jan 4, 2020
BACKGROUND: Despite their high accuracy to recognize oral potentially malignant disorders (OPMDs) with cancer risk, non-invasive oral assays are poor in discerning whether the risk is high or low. However, it is critical to identify the risk levels, ...
Radiomics in stratification of pancreatic cystic lesions: Machine learning in action.
Cancer letters
Oct 17, 2019
Pancreatic cystic lesions (PCLs) are well-known precursors of pancreatic cancer. Their diagnosis can be challenging as their behavior varies from benign to malignant disease. Precise and timely management of malignant pancreatic cysts might prevent t...
Endoscopic detection and differentiation of esophageal lesions using a deep neural network.
Gastrointestinal endoscopy
Oct 1, 2019
BACKGROUND AND AIMS: Diagnosing esophageal squamous cell carcinoma (SCC) depends on individual physician expertise and may be subject to interobserver variability. Therefore, we developed a computerized image-analysis system to detect and differentia...
Female
Reproducibility of Results
Aged
Aged, 80 and over
Humans
Neural Networks, Computer
Deep Learning
Image Processing, Computer-Assisted
Neoplasm Invasiveness
Esophagus
Adult
Sensitivity and Specificity
Male
Middle Aged
Esophageal Squamous Cell Carcinoma
Esophageal Diseases
Narrow Band Imaging
Esophageal Neoplasms
Observer Variation
Precancerous Conditions
Optical Imaging
Real-time automated diagnosis of precancerous lesions and early esophageal squamous cell carcinoma using a deep learning model (with videos).
Gastrointestinal endoscopy
Aug 21, 2019
BACKGROUND AND AIMS: We developed a system for computer-assisted diagnosis (CAD) for real-time automated diagnosis of precancerous lesions and early esophageal squamous cell carcinomas (ESCCs) to assist the diagnosis of esophageal cancer.
Deep-learning based detection of gastric precancerous conditions.
Gut
Aug 2, 2019
Semi-supervised adversarial model for benign-malignant lung nodule classification on chest CT.
Medical image analysis
Jul 10, 2019
Classification of benign-malignant lung nodules on chest CT is the most critical step in the early detection of lung cancer and prolongation of patient survival. Despite their success in image classification, deep convolutional neural networks (DCNNs...
Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.
Nature biomedical engineering
Oct 10, 2018
The detection and removal of precancerous polyps via colonoscopy is the gold standard for the prevention of colon cancer. However, the detection rate of adenomatous polyps can vary significantly among endoscopists. Here, we show that a machine-learni...
Determination of mammographic breast density using a deep convolutional neural network.
The British journal of radiology
Oct 1, 2018
OBJECTIVE: High breast density is a risk factor for breast cancer. The aim of this study was to develop a deep convolutional neural network (dCNN) for the automatic classification of breast density based on the mammographic appearance of the tissue a...
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