Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multi-modal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. This review article provides a factual listing of methods and summarizes the broad scientific challenges faced in the field of medical image fusion. We characterize the medical image fusion research based on (1) the widely used image fusion methods, (2) imaging modalities, and (3) imaging of organs that are under study. This review concludes that even though there exists several open ended technological and scientific challenges, the fusion of medical images has proved to be useful for advancing the clinical reliability of using medical imaging for medical diagnostics and analysis, and is a scientific discipline that has the potential to significantly grow in the coming years.

Medical Image Fusion: A survey of the state of the art

Medical image fusion: A survey of the state of the art

Image fusion is a well-recognized and a conventional field of image processing. Image fusion provides an efficient way of enhancing and combining pixel-level data resulting in highly informative data for human perception as compared with individual input source data. In this paper, we have demonstrated a comprehensive survey of multi-scale and non-multi-scale decomposition-based image fusion methods in detail. The reference-based and non-reference-based image quality evaluation metrics are summarized together with recent trends in image fusion. Several image fusion applications in various fields have also been reported. It has been stated that though a lot of singular fusion techniques seemed to have given optimum results, the focus of researchers is shifting toward amalgamated or hybrid fusion techniques, which could harness the attributes of both multi-scale and non-multi-scale decomposition methods. Toward the end, the review is concluded with various open challenges for researchers. Thus, the descriptive study in this paper would form basis for stimulating and nurturing advanced research ideas in image fusion.

From Multi-Scale Decomposition to Non-Multi-Scale Decomposition Methods: A Comprehensive Survey of Image Fusion Techniques and Its Applications

A new technique for image fusion based on nonsubsampled shearlet transform (NSST) and improved pulse-coupled neural network (PCNN) is proposed. NSST, as a novel multiscale geometric analysis tool, can be optimally efficient in representing images and capturing the geometric features of multidimensional data. As a result, NSST is introduced into the area of image fusion to complete the decompositions of source images in any scale and any direction. Then the basic PCNN model is improved to be improved PCNN (IPCNN), which is more concise and more effective. IPCNN adopts the contrast of each pixel in images as the linking strength β , and the time matrix T of subimages can be obtained via the synchronous pulse-burst property. By using IPCNN, the fused subimages can be achieved. Finally, the final fused image can be obtained by using inverse NSST. The numerical experiments demonstrate that the new technique presented in this paper is competitive in the field of image fusion in terms of both fusion performance and computational efficiency.

Technique for image fusion based on nonsubsampled shearlet transform and improved pulse-coupled neural network

Editorial: Information fusion in the realm of medical applications - A bibliographic glimpse at its growing appeal

The importance of information offered by the medical images for diagnosis support can be increased by combining images from different compatible medical devices. The fusion process allows combination of salient feature of these images. In this paper we present different techniques of image fusion, our work for medical image fusion based on discrete wavelet transform and how we understand to integrate this process into a distributed application. The dedicated application considers Java technology for using its facilities as a future development, regarding a remote access mechanism.

Medical image fusion based on discrete wavelet transform using Java technology

The issue of plagiarism is a much discussed topic in the nowadays academic environment. Since the inspiration sources are very vast and accessible, analyzing the originality can become extremely challenging for a human interpreter and therefore an automated solution is very welcomed. This article presents a cross-platform implementation that measures the similarities found between various source codes that are supposed to solve a certain specific software problem. The testing environment (groups of students) allows the quantified correlations to serve for increasing the awareness about the importance of originality during the code development process.

A cross-platform solution for software plagiarism detection

A web dedicated application is very useful for assisted diagnosis in healthcare domain. Medical images acquired with different medical image modalities contain important diagnostic information. The combination of complementary data from different images can lead to more important information. The fusion process allows combination of salient feature of these images. In this paper we present methods for medical image fusion, based on discrete wavelet transform. These methods are implemented in a web distributed application, using Java technology. The web dedicated application will integrate components able to be discovered in a ubiquitous computing system. The components are developed in dedicated Java packages that allow physicians to realize a fusion from a remote place. Considering radiology images we approve the functionality of the application by calculating significant quantitative parameters for fusion process evaluation.

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Medical Fusion Components for a Web Dedicated Application

Telepresence robots are a real solution for remote interaction with the physical environment. During the emergency situation created by the COVID-19 pandemic, telepresence robots were one of the useful solutions for the physical interaction of medical staff or relatives of patients with infected people. In this paper we analyze the possibility of creating mesh networks based on Li-Fi communications among telepresence robots, as a solution for emergencies with large-scale disasters, when the existing telecommunications infrastructure is down. We are analyzing the possibility of mobile telepresence robots to use, for data communications, a mesh network based on both Wi-Fi and Li-Fi technologies. We start from previous research in which data communications for mobile robots were made in the first stage via Bluetooth, then via Wi-Fi, and later Li-Fi technology was tested. It is also analyzed the possibility of medical telepresence robots to cover the need for technical equipment for post-disaster medical emergencies.

Mesh Networks with Interconnected Li-Fi and Wi-Fi Communications Applied to Telepresence Robots for Medical Emergency Situations

Oracle database offers the facility of searching and retrieving content-based multimedia objects such as audio, video, image or electronic documents, after a signature. There are different methods for signature generation for each specified object. The content-based image retrieval (CBIR) in Oracle may be realized on a linear search and comparison of the signatures using different parameters, or by image indexing, which are methods available in Enterprise Edition of Oracle Database. medBase is a dedicated application that uses Oracle interMedia for CBIR. Oracle has the possibility to integrate Java classes that offers more flexibility to a programmer in generating and processing the database objects. The chosen technology implemented in this paper is based on JSP, which is capable of realizing distributed web applications, and it can directly access the Java classes and methods offered by Oracle. The dedicated application was tested using different types of radiological images stored in an Oracle database.

Ligia Chiorean

Papers

Medical image fusion based on discrete wavelet transform using Java technology

A cross-platform solution for software plagiarism detection

Medical Fusion Components for a Web Dedicated Application

Mesh Networks with Interconnected Li-Fi and Wi-Fi Communications Applied to Telepresence Robots for Medical Emergency Situations

Radiology Database Images Retrieving