ADVANCED BONE TUMOR SEGMENTATION IN NOISY CT IMAGES USING  STOCHASTIC TUMOR SEGMENTATION NETWORK

RATHLA ROOPSINGH  DR. D. VASUMATHI

ADVANCED BONE TUMOR SEGMENTATION IN NOISY CT IMAGES USING STOCHASTIC TUMOR SEGMENTATION NETWORK

Authors

RATHLA ROOPSINGH DR. D. VASUMATHI

Keywords:

Bone tumor, computed tomography, stochastic clustering, feature learning, multi scale refinement method, noisy medical images, Markov Random Fields, automated diagnosis, tumor boundary refinement.

Abstract

Bone Tumors are a growth of cells within the bone that is one of the characteristics ofmalignant tumors. But, Due to noise interference, uneven shape of tumor, and different waysof appearance of the tissue, Segmenting bone tumors in computed tomography images is a challenging task. In this connection, present the Stochastic Tumor Segmentation

References

Peng, B., Guo, Z., Zhu, X., Ikeda, S., &Tsunoda, S. (2020, November). Semantic segmentation of femur bone from MRI images of patients with hematologic malignancies. In 2020 Ieee Region 10 Conference (Tencon) (pp. 1090-1094). IEEE.

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Published

2024-08-08

How to Cite

RATHLA ROOPSINGH DR. D. VASUMATHI. (2024). ADVANCED BONE TUMOR SEGMENTATION IN NOISY CT IMAGES USING STOCHASTIC TUMOR SEGMENTATION NETWORK . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 4698–4724. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2964