AIMC Topic: Observer Variation

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Semiautomatic Fetal Intelligent Navigation Echocardiography Has the Potential to Aid Cardiac Evaluations Even in Less Experienced Hands.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Aug 14, 2019
OBJECTIVES: To investigate the interobserver and intraobserver variability and corresponding learning curve in a semiautomatic approach for a standardized assessment of the fetal heart (fetal intelligent navigation echocardiography [FINE]).
Humans Artificial Intelligence Observer Variation Pregnancy Trimester, Second Heart Defects, Congenital Learning Curve Echocardiography, Four-Dimensional Pregnancy Female Ultrasonography, Prenatal Clinical Competence
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Performance of an artificial intelligence algorithm for reporting urine cytopathology.

Cancer cytopathology Aug 14, 2019
BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite The Paris System for Reporting Urinary Cytology, there still is poor interobserver agreement with ur...
Urine Urothelium Humans Feasibility Studies Female Image Interpretation, Computer-Assisted Aged Observer Variation Aged, 80 and over Sensitivity and Specificity Carcinoma, Transitional Cell Middle Aged Deep Learning Urinary Bladder Neoplasms
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Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images.

European journal of cancer (Oxford, England : 1990) Jul 18, 2019
BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reveals a high discordance between individual pathologists. For melanoma, the literature reports on 25-2...
Nevus Pathologists Microscopy Image Interpretation, Computer-Assisted Observer Variation Melanoma Skin Neoplasms Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Diagnosis, Differential Predictive Value of Tests Biopsy Humans
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Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study.

Eye (London, England) Jul 2, 2019
OBJECTIVES: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic optic disc photographs, and to compare this performance to the performance of a large cohort of ophthal...
Humans Artificial Intelligence Retrospective Studies Clinical Competence ROC Curve Europe Predictive Value of Tests Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Deep Learning Photography Ophthalmologists Observer Variation Optic Disk Glaucoma, Open-Angle Optic Nerve Diseases Optometrists False Positive Reactions
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Gastroenterologist-Level Identification of Small-Bowel Diseases and Normal Variants by Capsule Endoscopy Using a Deep-Learning Model.

Gastroenterology Jun 25, 2019
BACKGROUND & AIMS: Capsule endoscopy has revolutionized investigation of the small bowel. However, this technique produces a video that is 8-10 hours long, so analysis is time consuming for gastroenterologists. Deep convolutional neural networks (CNN...
Humans Prognosis Retrospective Studies Reproducibility of Results Deep Learning Capsule Endoscopy China Intestine, Small Clinical Competence Diagnosis, Differential Intestinal Diseases Gastroenterologists Predictive Value of Tests Image Interpretation, Computer-Assisted Observer Variation
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Deep learning assisted mitotic counting for breast cancer.

Laboratory investigation; a journal of technical methods and pathology Jun 20, 2019
As part of routine histological grading, for every invasive breast cancer the mitotic count is assessed by counting mitoses in the (visually selected) region with the highest proliferative activity. Because this procedure is prone to subjectivity, th...
Netherlands Humans Observer Variation Middle Aged Neural Networks, Computer Mitotic Index Diagnosis, Computer-Assisted Prospective Studies Aged Female Deep Learning Retrospective Studies Adult Reproducibility of Results Cohort Studies Breast Neoplasms
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Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net.

Medical physics May 29, 2019
PURPOSE: Transrectal ultrasound (TRUS) is a versatile and real-time imaging modality that is commonly used in image-guided prostate cancer interventions (e.g., biopsy and brachytherapy). Accurate segmentation of the prostate is key to biopsy needle p...
Observer Variation Ultrasonography Image Processing, Computer-Assisted Prostate Supervised Machine Learning Humans Male Deep Learning
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Benefits of deep learning for delineation of organs at risk in head and neck cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology May 27, 2019
PURPOSE/OBJECTIVE: Precise delineation of organs at risk (OARs) in head and neck cancer (HNC) is necessary for accurate radiotherapy. Although guidelines exist, significant interobserver variability (IOV) remains. The aim was to validate a 3D convolu...
Deep Learning Head and Neck Neoplasms Organs at Risk Observer Variation Humans Aged Neural Networks, Computer Female Aged, 80 and over Male Middle Aged
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Pathologist-level classification of histopathological melanoma images with deep neural networks.

European journal of cancer (Oxford, England : 1990) May 23, 2019
BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reveals a high discordance between individual pathologists. For melanoma, the literature reports 25-26% ...
Nevus Humans Melanoma Skin Neoplasms Reproducibility of Results Pathologists Diagnosis, Computer-Assisted Microscopy Deep Learning Image Interpretation, Computer-Assisted Predictive Value of Tests Observer Variation Biopsy
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Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections.

PloS one May 20, 2019
PURPOSE: To compare manual corrections of liver masks produced by a fully automatic segmentation method based on convolutional neural networks (CNN) with manual routine segmentations in MR images in terms of inter-observer variability and interaction...
Observer Variation Carcinoma, Hepatocellular Magnetic Resonance Imaging Liver Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Liver Neoplasms
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