Autors: Gancheva, V. S.
Title: Parallel Multithreaded Medical Images Filtering
Keywords: image filtering; medical images; multithreading; parallel co

Abstract: The quality of medical images is paramount. Being of high grade, it guarantees the quality of medical diagnosis, treatment and quality of patient's life through the means of health care or using automate intelligent systems for medical diagnosing, treatment and monitoring. The paper presents the computational challenges in medical images processing. The great challenges are to propose parallel computational models and parallel program implementations based on the algorithms for medical images filtering. Parallel computational model based on two-dimensional filters is designed. The proposed parallel model is verified by multithreaded parallel program implementation. An investigation of the efficiency of medical images filters based on parallel multithreaded program implementation, applying two-dimensional filters on a given list of compressed jpeg medical images and generating output jpeg images for each type of applied filter.

References

    Issue

    International Conference on Computational Science and Computational Intelligence, CSCI 2021, pp. 1788 - 1793, 2021, United States, DOI 10.1109/CSCI54926.2021.00338

    Цитирания (Citation/s):
    1. Li T., Nie Y., Wang Y., Ye M., Cao P., Xu Z., Wang Z., A Dense Sample Surface Defect Detection Algorithm Based on Deep Learning and Thread Pool 2023 5th International Conference on Frontiers Technology of Information and Computer, ICFTIC 2023, pp. 1159 - 1163, DOI: 10.1109/ICFTIC59930.2023.10455824 - 2023 - в издания, индексирани в Scopus или Web of Science
    2. Li T., Nie Y., Wang Y., Ye M., Cao P., Xu Z., Wang Z., A Dense Sample Surface Defect Detection Algorithm Based on Deep Learning and Thread Pool 2023 5th International Conference on Frontiers Technology of Information and Computer, ICFTIC 2023, pp. 1159 - 1163, DOI: 10.1109/ICFTIC59930.2023.10455824 - 2024 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus