• Manali Tayade
• Aron D’souza
• Jaykumar Patel,
• Selvakumar

Computer based image processing has played a huge role in medical image segmentation. Segmentation images are now used routinely in a multitude of different applications such as quantification of tissue, diagnosis, localization of pathology, study of anatomical structures, treatment planning, partial, volume correction of functional imaging data and computer imaging surgery. In particular, medical images are often corrupted by noise which can cause considerable difficulties when applying classical segmentation techniques such as edge detection and thresholding. Deformable image models have been studied and extensively used in medical image segmentation with promising results. Deformable models are curves or surface defined within an image domain that can be under the influence of internal forces, which are defined under the curve surface itself and also the external forces which are constructed from the image data. Making use of medical image segmentation and by constructing a deformable model approach, accurate and quantitative data can be efficiently extracted to support the spectrum of biomedical investigation and clinical activities, from diagnosis to radiotherapy as well as surgery.

deformable, image processing, segmentation

"Deformable Image Segmentation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.309-312, April-2019, Available :http://www.jetir.org/papers/JETIR1904C50.pdf

"Deformable Image Segmentation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp309-312, April-2019, Available at : http://www.jetir.org/papers/JETIR1904C50.pdf