Medical Imaging Importance in the Real World
Ramgopal Kashyap
Abstract
In the medical image resolution, automatic segmentation is a challenging task, and it's still an unsolved problem for most medical applications due to the wide variety connected with image modalities, encoding parameters, and organic variability. In this chapter, a review and critique of medical image segmentation using clustering, compression, histogram, edge detection, parametric, variational model. and level set-based methods is presented. Modes of segmentation like manual, semi-automatic, interactive, and automatic are also discussed. To present current challenges, aim and motivation for doing fast, interactive and correct segmentation, the medical image modalities X-ray, CT, MRI, and PET are discussed in this chapter.
Topics & Concepts
SegmentationArtificial intelligenceComputer scienceHistogramMedical imagingComputer visionImage segmentationCluster analysisScale-space segmentationImage (mathematics)Modality (human–computer interaction)ModalitiesSegmentation-based object categorizationPattern recognition (psychology)Social scienceSociologyBrain Tumor Detection and ClassificationAI in cancer detectionRadiomics and Machine Learning in Medical Imaging