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International Journal of Imaging Systems and Technology is a peer-reviewed journal published by Wiley, covering Medical Image Segmentation Techniques, AI in cancer detection, Brain Tumor Detection and Classification.
| Publisher | Wiley |
|---|---|
| Reference style | Author–year (Chicago) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." International Journal of Imaging Systems and Technology 12 (3): 45–58.
Formats any DOI in International Journal of Imaging Systems and Technology style. No sign-up. |
| Publishes research in | Medical Image Segmentation Techniques AI in cancer detection Brain Tumor Detection and Classification Radiomics and Machine Learning in Medical Imaging Advanced Neural Network Applications |
| ISSN | 0899-9457 |
| Citation impact (2-yr) | 2.59 |
| h-index | 76 |
| i10-index | 802 |
| Total citations | 35,216 |
| Article processing charge | $3,450 |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | onlinelibrary.wiley.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Abstract In recent years, diffusion‐weighted magnetic resonance imaging has attracted considerable attention due to its unique potential to delineate the white matter pathways of the brain. However, methodologies currently available and in common use among neuroscientists and clinicians are typically based on the diffusion tensor model, which has comprehensively been shown to be inadequate to…
Abstract Super‐Resolution reconstruction produces one or a set of high‐resolution images from a sequence of low‐resolution frames. This article reviews a variety of Super‐Resolution methods proposed in the last 20 years, and provides some insight into, and a summary of, our recent contributions to the general Super‐Resolution problem. In the process, a detailed study of…
The inverse conductivity problem is the mathematical problem that must be solved in order for electrical impedance tomography systems to be able to make images. Here we show how this inverse conductivity problem is related to a number of other inverse problems. We then explain the workings of an algorithm that we have used to…
Abstract A new method, based on an iterative procedure, for solving the two‐dimensional inverse scattering problem is presented. This method employs an equivalent Neumann series solution in each iteration step. The purpose of the algorithm is to provide a general method to solve the two‐dimensional imaging problem when the Born and the Rytov approximations break…
Abstract The X‐ray spectra of pure elements, excited using MeV energy beam of protons from the nuclear microprobe, have known spectra signatures. This makes X‐ray spectra for more complex mixtures amenable to decomposition into contributions from the component elements. By devising this procedure as a matrix operation that transforms directly from spectrum vector to elemental…
