AIMC Topic: Image Interpretation, Computer-Assisted

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A fully automated hybrid human sperm detection and classification system based on mobile-net and the performance comparison with conventional methods.

Medical & biological engineering & computing Mar 6, 2020
Sperm morphology, as an indicator of fertility, is a critical tool in semen analysis. In this study, a smartphone-based hybrid system that fully automates the sperm morphological analysis is introduced with the aim of eliminating unwanted human facto...
Male Deep Learning Smartphone Support Vector Machine Humans Neural Networks, Computer Young Adult Adult Wavelet Analysis Semen Analysis Spermatozoa Image Interpretation, Computer-Assisted
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BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Communications biology Mar 5, 2020
Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain organization and function can be describ...
Diffusion Tensor Imaging Neocortex Artificial Intelligence Reproducibility of Results Magnetic Resonance Imaging Brain Mapping Predictive Value of Tests Workflow Image Interpretation, Computer-Assisted Nerve Net Humans
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Deep learning approach to classification of lung cytological images: Two-step training using actual and synthesized images by progressive growing of generative adversarial networks.

PloS one Mar 5, 2020
Cytology is the first pathological examination performed in the diagnosis of lung cancer. In our previous study, we introduced a deep convolutional neural network (DCNN) to automatically classify cytological images as images with benign or malignant ...
Image Interpretation, Computer-Assisted Deep Learning Humans Image Processing, Computer-Assisted Lung Neoplasms Male Data Accuracy Lung
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Deep learning computer vision algorithm for detecting kidney stone composition.

BJU international Mar 3, 2020
OBJECTIVES: To assess the recall of a deep learning (DL) method to automatically detect kidney stones composition from digital photographs of stones.
Photography Cystine Calcium Oxalate Struvite Calcium Phosphates Image Interpretation, Computer-Assisted Kidney Calculi Humans Algorithms Deep Learning ROC Curve Uric Acid
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Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.

European journal of radiology Mar 2, 2020
PURPOSE: To evaluate the performance of machine-learning-based computed tomography (CT) radiomic analysis to differentiate high-risk thymic epithelial tumours (TETs) from low-risk TETs according to the WHO classification.
Tomography, X-Ray Computed Female Aged Young Adult Adult Male Middle Aged Neoplasms, Glandular and Epithelial ROC Curve Area Under Curve Humans Image Interpretation, Computer-Assisted Thymus Neoplasms Machine Learning Thymus Gland Retrospective Studies
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DeepSurvNet: deep survival convolutional network for brain cancer survival rate classification based on histopathological images.

Medical & biological engineering & computing Mar 2, 2020
Histopathological whole slide images of haematoxylin and eosin (H&E)-stained biopsies contain valuable information with relation to cancer disease and its clinical outcomes. Still, there are no highly accurate automated methods to correlate histolopa...
Image Interpretation, Computer-Assisted Histocytochemistry Neural Networks, Computer Brain Neoplasms Deep Learning Survival Analysis Humans
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Fusing Self-Organized Neural Network and Keypoint Clustering for Localized Real-Time Background Subtraction.

International journal of neural systems Mar 2, 2020
Moving object detection in video streams plays a key role in many computer vision applications. In particular, separation between background and foreground items represents a main prerequisite to carry out more complex tasks, such as object classific...
Image Interpretation, Computer-Assisted Humans Datasets as Topic Neural Networks, Computer Pattern Recognition, Automated Models, Theoretical Subtraction Technique Cluster Analysis
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Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.

JAMA network open Mar 2, 2020
IMPORTANCE: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives.
Female Sweden Mammography Aged Radiology Adult Radiologists Sensitivity and Specificity Humans Image Interpretation, Computer-Assisted Breast Neoplasms Deep Learning Artificial Intelligence Middle Aged United States Algorithms Early Detection of Cancer
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Multimodal Image Analysis for Assessing Multiple Sclerosis and Future Prospects Powered by Artificial Intelligence.

Seminars in ultrasound, CT, and MR Feb 29, 2020
The purpose of this paper is to serve as a template for greater understanding for the practicing radiologist about key steps to perform multimodality computer analysis of MRI images, specifically in multiple sclerosis patients. With this understandin...
Image Interpretation, Computer-Assisted Humans Brain Magnetic Resonance Imaging Artificial Intelligence Multimodal Imaging Multiple Sclerosis
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Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.

Gastroenterology Feb 29, 2020
BACKGROUND & AIMS: Narrow-band imaging (NBI) can be used to determine whether colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial intelligence (AI) system can increase the accuracy of characterizations of polyps b...
Narrow Band Imaging Visual Perception Seoul Colorectal Neoplasms Adenomatous Polyps Colonoscopy Colonic Polyps Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted Clinical Competence Humans Deep Learning Observer Variation Predictive Value of Tests Reproducibility of Results Hyperplasia Workflow
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