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AI-Assisted Annotation of Medical Images

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dc.contributor.authorDewan, Suhaen
dc.contributor.authorZhou, Daodaoen
dc.contributor.authorHuynh, Longen
dc.contributor.authorGuo, Zipengen
dc.date.accessioned2022-12-15T23:22:55Zen
dc.date.available2022-12-15T23:22:55Zen
dc.date.issued2022-12-15en
dc.description.abstractIn digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments. More precisely, it’s the process of assigning a label to every pixel in an image so that pixels with the same label share certain characteristics. Image segmentation is an important step in almost any medical image study. Segments are used in images from microscopes that show us different types of cells and these cells contain hundreds of organelles and macromolecular assemblies. Cell Segmentation is the task of splitting a microscopic image domain into lots of different segments, which represent individual instances of cells, however, this requires enormous time for domain experts to label manually and thus the need for AI-Assisted annotation of medical Images. Our project will aid the annotators in receiving images quickly and easily through our web application and performing the predictions on these images.en
dc.description.notesMedicalImagingAIreport.docx - Final report (Word version) MedicalImagingAIreport.pdf - Final report (PDF version) MedicalImagingAIpresentation.pptx - Final presentation (PowerPoint version) MedicalImagingAIpresentation.pdf - Final presentation (PDF version)en
dc.identifier.urihttp://hdl.handle.net/10919/112913en
dc.language.isoen_USen
dc.publisherVirginia Techen
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectWebsiteen
dc.subjectSegmentationen
dc.subjectAWSen
dc.subjectAIen
dc.subjectReacten
dc.subjectCellsen
dc.subjectMedicalen
dc.subjectMicroscopicen
dc.titleAI-Assisted Annotation of Medical Imagesen
dc.typePresentationen
dc.typeReporten

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