Diagnosis of Abdominal Diseases Affecting Major Organs Using CT Image and YOLOV8

Main Article Content

Mrs. K. Ramanandhini
Mr. Pandiarajan S

Abstract

This study investigates the YOLOv8 method, a popular object detection model, to detect abnormalities in abdominal CT scans. Our study leverages the sophisticated architecture and point-of- care detection capabilities of YOLOv8 to show that the model improves diagnostic accuracy and helps radiologists quickly identify potential panic cases

Downloads

Download data is not yet available.

Article Details

How to Cite
[1]
Mrs. K. Ramanandhini and Mr. Pandiarajan S , Trans., “Diagnosis of Abdominal Diseases Affecting Major Organs Using CT Image and YOLOV8”, IJPMH, vol. 5, no. 2, pp. 17–19, Jan. 2025, doi: 10.54105/ijpmh.B1050.05020125.
Section
Articles

How to Cite

[1]
Mrs. K. Ramanandhini and Mr. Pandiarajan S , Trans., “Diagnosis of Abdominal Diseases Affecting Major Organs Using CT Image and YOLOV8”, IJPMH, vol. 5, no. 2, pp. 17–19, Jan. 2025, doi: 10.54105/ijpmh.B1050.05020125.
Share |

References

Sabri Koçer; Omar Mohamed; Özgür Dündar (2024) “Disease Detection in Abdominal CT Images Using the YOLOv5 Algorithm: A Deep Learning Approach” DOI: https://dx.doi.org/10.1109/ICEST62335.2024.10639613

Litjens, G., et al. (2017). "A survey on deep learning in medical image analysis." Medical Image Analysis, 42, 60-88. DOI: https://doi.org/10.1016/j.media.2017.07.005

Redmon, J., et al. (2016). "You Only Look Once: Unified, Real- Time Object Detection." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. DOI: https://doi.org/10.1109/CVPR.2016.91

Bochkovskiy, A., et al. (2020). "YOLOv4: Optimal Speed and Accuracy of Object Detection." arXiv preprint arXiv:2004.10934. DOI: https://dx.doi.org/10.48550/arXiv.2004.10934

Priyanka Israni, Maulika S. Patel, Medical Image Analysis (MedIA) using Deep Learning. (2020). In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 7S, pp. 21–25). DOI: https://doi.org/10.35940/ijitee.g1007.0597s20

C. Devi Parameswari, K. Shankar, Medical Image Security - the State-of-the-Art. (2019). In International Journal of Recent Technology and Engineering (Vol. 8, Issue 4S2, pp. 542–545). DOI: https://doi.org/10.35940/ijrte.d1101.1284s219

Akila, Mrs. P. G., Batri, K., Sasi, G., & Ambika, R. (2019). Denoising of MRI Brain Images using Adaptive Clahe Filtering Method. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 1s, pp. 91–95). DOI: https://doi.org/10.35940/ijeat.a1018.1091s19

Saha, T., & Vishal, Dr. K. (2024). A Study of Application of Digital Image Processing in Medical Field and Medical Image Segmentation by Edge Detection. In International Journal of Emerging Science and Engineering (Vol. 12, Issue 4, pp. 3–8). DOI: https://doi.org/10.35940/ijese.g9890.12040324