TY - GEN
T1 - Platform for Pathology Marking and Analysis, Applied to Medical Imaging
AU - Lizana-Cortez, Sergio
AU - Auccahuasi, Wilver
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Nowadays, with the exploitation of artificial intelligence, the registration and identification of pathologies in medical images is required. In the present work we develop a platform for the tagging of pathologies found in medical images, the system is designed to provide physicians with an efficient and accurate tool for the diagnosis and monitoring of various diseases. Using Python as the main programming language, libraries such as SimpleITK for image analysis and Django for the creation of a user-friendly web interface will be used. The integration of LabelMe will allow users to mark regions of interest in medical images such as X-rays, mammograms, CT scans, MRI images among other imaging modalities, in the various image formats such as DICOM and NRRD formats. The system will allow the marking of images by medical specialists, as well as the analysis of the markings to locate areas where they coincide by more than two physicians. The platform is designed for the marking of multiple images in different formats and modalities.
AB - Nowadays, with the exploitation of artificial intelligence, the registration and identification of pathologies in medical images is required. In the present work we develop a platform for the tagging of pathologies found in medical images, the system is designed to provide physicians with an efficient and accurate tool for the diagnosis and monitoring of various diseases. Using Python as the main programming language, libraries such as SimpleITK for image analysis and Django for the creation of a user-friendly web interface will be used. The integration of LabelMe will allow users to mark regions of interest in medical images such as X-rays, mammograms, CT scans, MRI images among other imaging modalities, in the various image formats such as DICOM and NRRD formats. The system will allow the marking of images by medical specialists, as well as the analysis of the markings to locate areas where they coincide by more than two physicians. The platform is designed for the marking of multiple images in different formats and modalities.
KW - HPC
KW - Slurm
KW - configuration
KW - development
KW - processing
KW - video
UR - http://www.scopus.com/inward/record.url?scp=85217181745&partnerID=8YFLogxK
U2 - 10.1109/ICICNIS64247.2024.10823142
DO - 10.1109/ICICNIS64247.2024.10823142
M3 - Contribución a la conferencia
AN - SCOPUS:85217181745
T3 - Proceedings of 5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024
SP - 980
EP - 985
BT - Proceedings of 5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024
Y2 - 17 December 2024 through 18 December 2024
ER -