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An Overview and Application of Deep Convolutional Neural Networks for Medical Image Segmentation

Sanskruti Patel

202320 citationsDOI

Abstract

Medical imaging technologies are widely utilized as a non-invasive diagnostic process that helps professionals identify diseases and injuries. Convolutional neural networks (CNNs) have become increasingly popular since they are considered to be the best approach for a variety of computer vision problems includes medical imaging and diagnostics. Image segmentation using CNN models makes image analysis easier that can effectively use with different image modalities like X-ray, MRI, CT, Ultrasound and PET. This review article provides a perspective on using CNN models for various medical image segmentation tasks. It contains the details of benchmark deep CNN models available for image segmentation, publicly available medical imaging datasets and various applications of deep CNN models for medical image segmentation tasks.

Topics & Concepts

Convolutional neural networkComputer scienceArtificial intelligenceMedical imagingSegmentationBenchmark (surveying)Image segmentationDeep learningMedical ultrasoundComputer visionPerspective (graphical)Process (computing)Image (mathematics)Pattern recognition (psychology)RadiologyMedicineUltrasoundOperating systemGeographyGeodesyCOVID-19 diagnosis using AIAdvanced Neural Network ApplicationsAI in cancer detection