An Improved K-Means Clustering for Segmentation of Pancreatic Tumor from CT Images
Author:
Affiliation:
1. Department of IT, Easwari Engineering College, Chennai, India
2. Department of CSE, Easwari Engineering College, Chennai, India
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Computer Science Applications,Theoretical Computer Science
Link
https://www.tandfonline.com/doi/pdf/10.1080/03772063.2021.1944335
Reference23 articles.
1. Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans
2. A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling
3. DRINet for Medical Image Segmentation
4. A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans
5. Deep Supervision for Pancreatic Cyst Segmentation in Abdominal CT Scans
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1. DRL-based dependent task offloading with delay-energy tradeoff in medical image edge computing;Complex & Intelligent Systems;2024-01-29
2. State-of-Art Techniques for effective Segmentation and Classification of Pancreatic Cancer Using Deep Learning: A Review;2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS);2023-12-14
3. Automatic Segmentation of Pancreas and Pancreatic Tumor: A Review of a Decade of Research;IEEE Access;2023
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