Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Telemedicine
and smart healthcare systems have emerged as transformative solutions to bridge
the gap between medical expertise and underserved populations, particularly in
remote or rural areas. At the heart of this transformation lies medical image
processing, which aids in early diagnosis, effective monitoring, and timely
treatment of diseases. This survey paper investigates the latest advancements
in image processing techniques, with a particular focus on segmentation, shape
analysis, texture analysis, compression, and fusion of multimodal medical
images. In the diagnosis of brain tumors and other critical ailments, accurate
segmentation helps distinguish between benign and malignant growths, while
shape and texture descriptors enhance diagnostic confidence. Image compression,
especially lossless techniques, facilitates secure and efficient transmission of
medical data in telemedicine environments. Furthermore, image fusion integrates
complementary information from multiple imaging modalities like MRI, CT, PET,
and SPECT, offering a holistic view of the patient's condition. By referencing
state-of-the-art methods published in IEEE, Springer, and Elsevier journals
from 2024 and 2025, this paper offers a comprehensive overview of research
trends and identifies challenges in the domain. The study also explores how
these techniques contribute to the development of real-time,
hardware-integrated smart healthcare systems, paving the way for more
accessible and effective clinical services through telemedicine.
Country : India
IRJIET, Volume 9, Special Issue of ICCIS-2025 May 2025 pp. 61-69