AI Medical Compendium Topic

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Observer Variation

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Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI.

European radiology
OBJECTIVES: Prostate volume (PV) in combination with prostate specific antigen (PSA) yields PSA density which is an increasingly important biomarker. Calculating PV from MRI is a time-consuming, radiologist-dependent task. The aim of this study was t...

Effect of AI-assisted software on inter- and intra-observer variability for the X-ray bone age assessment of preschool children.

BMC pediatrics
BACKGROUND: With the rapid development of deep learning algorithms and the rapid improvement of computer hardware in the past few years, AI-assisted diagnosis software for bone age has achieved good diagnostic performance. The purpose of this study w...

Echocardiography Segmentation With Enforced Temporal Consistency.

IEEE transactions on medical imaging
Convolutional neural networks (CNN) have demonstrated their ability to segment 2D cardiac ultrasound images. However, despite recent successes according to which the intra-observer variability on end-diastole and end-systole images has been reached, ...

Deep learning multi-organ segmentation for whole mouse cryo-images including a comparison of 2D and 3D deep networks.

Scientific reports
Cryo-imaging provided 3D whole-mouse microscopic color anatomy and fluorescence images that enables biotechnology applications (e.g., stem cells and metastatic cancer). In this report, we compared three methods of organ segmentation: 2D U-Net with 2D...

Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images.

Scientific reports
Breast cancer tumor grade is strongly associated with patient survival. In current clinical practice, pathologists assign tumor grade after visual analysis of tissue specimens. However, different studies show significant inter-observer variation in b...

Fully automated mouse echocardiography analysis using deep convolutional neural networks.

American journal of physiology. Heart and circulatory physiology
Echocardiography (echo) is a translationally relevant ultrasound imaging modality widely used to assess cardiac structure and function in preclinical models of heart failure (HF) during research and drug development. Although echo is a very valuable ...

Tracked 3D ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry.

PloS one
Thyroid volumetry is crucial in the diagnosis, treatment, and monitoring of thyroid diseases. However, conventional thyroid volumetry with 2D ultrasound is highly operator-dependent. This study compares 2D and tracked 3D ultrasound with an automatic ...

Deep learning-based tool affects reproducibility of pes planus radiographic assessment.

Scientific reports
Angle measurement methods for measuring pes planus may lose consistency by errors between observers. If the feature points for angle measurement can be provided in advance with the algorithm developed through the deep learning method, it is thought t...

Automatic segmentation of thoracic CT images using three deep learning models.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
PURPOSE: Deep learning (DL) techniques are widely used in medical imaging and in particular for segmentation. Indeed, manual segmentation of organs at risk (OARs) is time-consuming and suffers from inter- and intra-observer segmentation variability. ...