AIMC Topic:
Image Interpretation, Computer-Assisted
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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...
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.
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...
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...
Reproducibility of Results
Colorectal Neoplasms
Colonoscopy
Clinical Competence
Predictive Value of Tests
Diagnosis, Computer-Assisted
Deep Learning
Adenomatous Polyps
Humans
Observer Variation
Narrow Band Imaging
Hyperplasia
Visual Perception
Workflow
Seoul
Colonic Polyps
Image Interpretation, Computer-Assisted
GP-CNN-DTEL: Global-Part CNN Model With Data-Transformed Ensemble Learning for Skin Lesion Classification.
IEEE journal of biomedical and health informatics
Feb 28, 2020
Precise skin lesion classification is still challenging due to two problems, i.e., (1) inter-class similarity and intra-class variation of skin lesion images, and (2) the weak generalization ability of single Deep Convolutional Neural Network trained...
Big data in IBD: big progress for clinical practice.
Gut
Feb 28, 2020
IBD is a complex multifactorial inflammatory disease of the gut driven by extrinsic and intrinsic factors, including host genetics, the immune system, environmental factors and the gut microbiome. Technological advancements such as next-generation se...
A novel CNN based Alzheimer's disease classification using hybrid enhanced ICA segmented gray matter of MRI.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 28, 2020
Predicting Alzheimer's Disease (AD) from Mild Cognitive Impairment (MCI) and Cognitive Normal (CN) has become wide. Recent advancement in neuroimaging in adoption with machine learning techniques are especially useful for pattern recognition of medic...
Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions.
BioMed research international
Feb 27, 2020
Breast cancer is the most diagnosed cancer among women around the world. The development of computer-aided diagnosis tools is essential to help pathologists to accurately interpret and discriminate between malignant and benign tumors. This paper prop...
Imaging research in fibrotic lung disease; applying deep learning to unsolved problems.
The Lancet. Respiratory medicine
Feb 25, 2020
Over the past decade, there has been a groundswell of research interest in computer-based methods for objectively quantifying fibrotic lung disease on high resolution CT of the chest. In the past 5 years, the arrival of deep learning-based image anal...
Software-assisted decision support in digital histopathology.
The Journal of pathology
Feb 25, 2020
Tissue diagnostics is the world of pathologists, and it is increasingly becoming digitalised to leverage the enormous potential of personalised medicine and of stratifying patients, enabling the administration of modern therapies. Therefore, the dail...
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