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Medical image processing is one of the real research regions in the most recent four decades. Segmentation partitions an image into constituent parts. This basic operation helps to analyze and interpret a certain region of interest of an image. Image segmentation helps in diagnosing abnormality in brain or any part of the body from the MRI scan or PET scan. Presently MRI is the most popular clinical diagnostic procedure for detection of any brain disorder, as it is a complete non-invasive method. Moreover, its ability to produce high resolution spatial images and its sensitivity towards differentiating neurological tissues help in diagnosis, prognosis, pre-surgical and post-surgical treatment planning for various diseases. If image segmentation can be done in an effective way, then the lesions, or the disorder, if present, can be classified to an effectual micro-level. This book presents a fast and efficient nature inspired optimization approaches for the optimal selection of threshold levels for brain MR image pre segmentation. We hope this book is most useful for the researchers and masters level students who were in the area of digital image processing.
| Autorius: | Satish Kumar Injeti, Sowjanya Kotte, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2019 |
| Knygos puslapių skaičius: | 96 |
| ISBN-10: | 6139970466 |
| ISBN-13: | 9786139970469 |
| Formatas: | 220 x 150 x 6 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Optimal Multilevel Threshold Selection for Brain MR Image Segmentation: Optimal MR Image Thresholding using bio and nature inspired algorithms“
