Special Issue on “Medical Imaging & Image Processing II”

Abstract

Medical Imaging is becoming an essential component in various fields of bio-medical research and clinical practice: Neuroscientists detect regional metabolic brain activity from positron emission tomography (PET), functional magnetic resonance imaging (MRI), and magnetic resonance spectrum imaging (MRSI) scans; biologists study cells and generate 3D confocal microscopy data sets; virologists generate 3D reconstructions of viruses from micrographs; and radiologists identify and quantify tumors from MRI and computed tomography (CT) scans.On the other hand, Image Processing includes the analysis, enhancement, and display of biomedical images. Image reconstruction and modeling techniques allow instant processing of 2D signals to create 3D images. Image processing and analysis can be used to determine the diameter, volume, and vasculature of a tumor or organ, flow parameters of blood or other fluids, and microscopic changes that have yet to raise any otherwise discernible flags. Image classification techniques help to detect subjects suffered from particular diseases and to detect disease-related regions.This Special Issue of Technologies comprises 4 selected papers about medical imaging and image processing. The first paper by Rashid et al.[1] investigated telemedicine, which is defined as the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes had the risk of confidentiality, ownership identity, and authenticity. In their paper, a data-hiding technique for ePHI/R was proposed. The color information in the cover image was used for key generation, and stego-images were produced with an ideal case. As a result, the whole stego-system was perfectly secure. This method included the features of watermarking and steganography techniques. Their method was applied to radiographic images. For the radiographic images, their method resembled watermarking, which was an ePHI/R data system. Experiments showed promising results for the application of their method to radiographic images in ePHI/R for both transmission and storage purposes.The second paper by Boudjelal et al.[2] stated that positron emission tomography (PET) is an imaging technique that generates 3D detail of physiological processes at the cellular level. This technique requires a radioactive tracer, which decays and releases a positron that collides with an electron; consequently, annihilation photons are emitted, which can be measured. The purpose of PET is to use the measurement of photons to reconstruct the distribution of radioisotopes in the body. Currently, PET is undergoing a revamp, with advancements in data measurement instruments and the computing methods used to create the images. These computer methods are required to solve the inverse problem of "image reconstruction from projection". In this paper, the authors proposed a novel kernel-based regularization technique for maximum-likelihood expe...

The emergence of new trends in clinical laboratory diagnosis

“… 5 , 6 These computational approaches enable proper visualization of organs without the need for invasive surgical techniques, thereby resulting in rapid and reliable disease diagnosis, and consequently increasing patient survival rates. 7 …”