Analysis of CT DICOM Image Segmentation for Abnormality Detection | Zendy

Rashmi Kulkarni | Zendy; K Bhavani | Zendy

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Analysis of CT DICOM Image Segmentation for Abnormality Detection

Author(s) -

Rashmi Kulkarni,

K Bhavani

Publication year - 2019

Publication title -

international journal of engineering and manufacturing

Language(s) - English

Resource type - Journals

eISSN - 2306-5982

pISSN - 2305-3631

DOI - 10.5815/ijem.2019.05.04

Subject(s) - segmentation , artificial intelligence , computer vision , computer science , abnormality , image segmentation , image processing , dicom , modality (human–computer interaction) , image (mathematics) , medicine , radiology , psychiatry

The cancer is a menacing disease. More care is required while diagnosing cancer disease. Mostly CT modality is used for Cancer therapy. Image processing techniques [1] can help doctors to diagnose easily and more accurately. Image pre-processing [2], segmentation methods [3] are used in extraction of cancerous nodules from CT images. Many researches have been done on segmentation of CT images with different algorithms, but they failed to reach 100% accuracy. This research work, proposes a model for analysis of CT image segmentation with filtered and without filtered images. And brings out the importance of pre-processing of CT images.

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