Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images.
Naveen PaluruAveen DayalHåvard Bjørke JenssenTomas SakinisLinga Reddy CenkeramaddiJaya PrakashPhaneendra K. YalavarthyPublished in: IEEE Trans. Neural Networks Learn. Syst. (2021)
Keyphrases
- lightweight
- ct images
- medical images
- lung nodules
- computed tomography
- medical imaging
- liver segmentation
- pet ct
- fracture detection
- computer tomography
- pulmonary nodules
- ct scans
- lymph nodes
- bone segmentation
- x ray
- pet images
- anatomical knowledge
- anatomical structures
- computer aided diagnosis
- medical image segmentation
- x ray images
- lung cancer
- low dose
- ct data
- lung parenchyma
- mr images
- magnetic resonance imaging
- computer aided detection
- medical image analysis
- ground glass opacity
- segmentation algorithm
- region of interest
- magnetic resonance images
- imaging modalities
- treatment planning
- segmentation method
- magnetic resonance
- region growing
- automatic segmentation
- automated segmentation
- image analysis
- image segmentation
- medical image processing
- image reconstruction
- ct imaging
- level set