AIMC Topic: Observer Variation

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Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.

Gastroenterology Jun 18, 2018
BACKGROUND & AIMS: The benefit of colonoscopy for colorectal cancer prevention depends on the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate, which is estimated to be higher than 50% in the screening-age population. ...
Prognosis Reproducibility of Results Colorectal Neoplasms Colonoscopy Diagnosis, Computer-Assisted Humans Neural Networks, Computer Machine Learning Colonic Polyps Video Recording Image Interpretation, Computer-Assisted Observer Variation Adenomatous Polyps ROC Curve Early Detection of Cancer Predictive Value of Tests Area Under Curve Feasibility Studies
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Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images.

PloS one May 9, 2018
In pathology, Immunohistochemical staining (IHC) of tissue sections is regularly used to diagnose and grade malignant tumors. Typically, IHC stain interpretation is rendered by a trained pathologist using a manual method, which consists of counting e...
Ki-67 Antigen Image Processing, Computer-Assisted Antigens, Neoplasm Observer Variation Immunohistochemistry Phantoms, Imaging Humans Neural Networks, Computer Female
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Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis.

Computers in biology and medicine Apr 27, 2018
A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming the diagnosis process of celiac disease which is primarily based on histological examination of biop...
Celiac Disease Image Processing, Computer-Assisted Duodenum Machine Learning Decision Making Humans Image Interpretation, Computer-Assisted Algorithms Biopsy Neural Networks, Computer Observer Variation Endoscopy Automation Diagnosis, Computer-Assisted Pattern Recognition, Automated Deep Learning Gastroscopy
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Using support vector machine analysis to assess PartinMR: A new prediction model for organ-confined prostate cancer.

Journal of magnetic resonance imaging : JMRI Feb 13, 2018
BACKGROUND: Partin tables represent the most widely used predictive tool for prostate cancer stage at prostatectomy but with potential limitations.
Humans Software Algorithms Retrospective Studies Reproducibility of Results Support Vector Machine Magnetic Resonance Imaging Area Under Curve Prostatic Neoplasms Biopsy Aged Male Middle Aged Image Processing, Computer-Assisted Observer Variation Proportional Hazards Models
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Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function.

International journal of radiation oncology, biology, physics Feb 7, 2018
PURPOSE: Automating and standardizing the contouring of clinical target volumes (CTVs) can reduce interphysician variability, which is one of the largest sources of uncertainty in head and neck radiation therapy. In addition to using uniform margin e...
Head and Neck Neoplasms Tumor Burden Observer Variation Oropharyngeal Neoplasms Humans Algorithms Deep Learning
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Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study.

The British journal of radiology Jan 10, 2018
OBJECTIVE: To train a generic deep learning software (DLS) to classify breast cancer on ultrasound images and to compare its performance to human readers with variable breast imaging experience.
Aged Clinical Competence Adolescent Aged, 80 and over Switzerland Humans Adult Ultrasonography, Mammary Image Interpretation, Computer-Assisted Breast Neoplasms Machine Learning Middle Aged Observer Variation Software Algorithms Retrospective Studies Female
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Quantitative Assessment of the Physiological Parameters Influencing QT Interval Response to Medication: Application of Computational Intelligence Tools.

Computational and mathematical methods in medicine Jan 4, 2018
Human heart electrophysiology is complex biological phenomenon, which is indirectly assessed by the measured ECG signal. ECG trace is further analyzed to derive interpretable surrogates including QT interval, QRS complex, PR interval, and T wave morp...
Humans Myocytes, Cardiac Observer Variation Artificial Intelligence Clinical Trials as Topic Software Calcium Cell Membrane Arrhythmias, Cardiac Ions Algorithms Sodium Reproducibility of Results Programming Languages Risk Regression Analysis Electrocardiography Electrophysiology Action Potentials Heart Terfenadine Models, Statistical Potassium Anti-Arrhythmia Agents
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Fully automated, deep learning segmentation of oxygen-induced retinopathy images.

JCI insight Dec 21, 2017
Oxygen-induced retinopathy (OIR) is a widely used model to study ischemia-driven neovascularization (NV) in the retina and to serve in proof-of-concept studies in evaluating antiangiogenic drugs for ocular, as well as nonocular, diseases. The primary...
Oxygen Observer Variation Deep Learning Algorithms Mice, Transgenic Image Processing, Computer-Assisted Female Retinal Neovascularization Microscopy, Confocal Animals Disease Models, Animal Male Mice, Inbred C57BL
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A method to combine target volume data from 3D and 4D planned thoracic radiotherapy patient cohorts for machine learning applications.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Dec 6, 2017
BACKGROUND AND PURPOSE: The gross tumour volume (GTV) is predictive of clinical outcome and consequently features in many machine-learned models. 4D-planning, however, has prompted substitution of the GTV with the internal gross target volume (iGTV)....
Four-Dimensional Computed Tomography Carcinoma, Non-Small-Cell Lung Humans Models, Statistical Machine Learning Radiotherapy Planning, Computer-Assisted Cohort Studies Tumor Burden Lung Neoplasms Observer Variation
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Reliability of an automatic classifier for brain enlarged perivascular spaces burden and comparison with human performance.

Clinical science (London, England : 1979) Jun 28, 2017
In the brain, enlarged perivascular spaces (PVS) relate to cerebral small vessel disease (SVD), poor cognition, inflammation and hypertension. We propose a fully automatic scheme that uses a support vector machine (SVM) to classify the burden of PVS ...
Stroke Observer Variation Humans Atrophy ROC Curve Reproducibility of Results Basal Ganglia Image Processing, Computer-Assisted Aged Cerebral Small Vessel Diseases Support Vector Machine Sensitivity and Specificity Magnetic Resonance Imaging Middle Aged
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