A review on region of interest-based hybrid medical image compression algorithms

Abstract

Digital medical images have become a vital resource that supports decision-making and treatment procedures in healthcare facilities. The medical image consumes large sizes of memory, and the size keeps on growth due to the trend of medical image technology. The technology of telemedicine encourages the medical practitioner to share the medical image to support knowledge sharing to diagnose and analyse the image. The healthcare system needs to ensure distributes the medical image accurately with zero loss of information, fast and secure. Image compression is beneficial in ensuring that achieve the goal of sharing this data. The region of interest-based hybrid medical compression algorithm plays the parts to reduce the image size and shorten the time of medical image compression process. Various studies have enhanced by combining numerous techniques to get an ideal result. This paper reviews the previous works conducted on a region of interest-based hybrid medical image compression algorithms.

Enhancement of digitized X-ray films using Contrast-Limited Adaptive Histogram Equalization (CLAHE)

“…19 A hybrid compression combines both lossless and lossy based on region of interest (ROI) and non-ROI of images. 20 However, in the absence of subject experts, the ROI could not be determined [21][22][23] as in our work.…”

Sunfa Ata Zuyan machine learning models for moon phase detection: algorithm, prototype and performance comparison

“…This algorithm works by using OpenCV API and can detect the shape of objects in the photo. For better accuracy, need to specify the target to classify the detected objects [8], [14], [33], [34].…”

Mobile design for medical care and minor emergencies applying telemedicine

“…Education is of great importance in such a way that learning first aid as well as the resolution of some emergencies is very efficient for families living in rural areas that can hardly be attended by a specialist [15], [16]. In Peru, as in other Latin American countries, scheduling appointments is complex due to long lines in person and the difficulty of coordinating the agendas of patients and physicians who are available to be scheduled for patient care [17]- [21]. The lack of education and the use of advanced technologies for medicine are not taken full advantage of, as they would solve the problems in hospitals by providing quality scheduling and care to patients [22], [23].…”