Wavelets and Imaging Informatics: A Review of the Literature
TLDR
A survey of the most significant practical and theoretical advances in the field of wavelet-based imaging informatics can be found in this paper, where the authors present a review of the wavelet transforms used for biomedical imaging.About:
This article is published in Journal of Biomedical Informatics.The article was published on 2001-04-01 and is currently open access. It has received 50 citations till now. The article focuses on the topics: Imaging informatics & Imaging technology.read more
Citations
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Journal ArticleDOI
A Pattern Similarity Scheme for Medical Image Retrieval
Dimitris K. Iakovidis,Nikos Pelekis,Evangelos E. Kotsifakos,Ioannis Kopanakis,Haralampos Karanikas,Yannis Theodoridis +5 more
TL;DR: It is shown that the proposed scheme can be efficiently and effectively applied for medical image retrieval from large databases, providing unsupervised semantic interpretation of the results, which can be further extended by knowledge representation methodologies.
Journal ArticleDOI
Radiomic features and multilayer perceptron network classifier: a robust MRI classification strategy for distinguishing glioblastoma from primary central nervous system lymphoma
TL;DR: The results reveal that a combination of radiomic features and MLP network classifier serves a high-performing and generalizable model for classification task for a small dataset with heterogeneous MRI protocols.
Journal ArticleDOI
Wavelet-Based Compression With ROI Coding Support for Mobile Access to DICOM Images Over Heterogeneous Radio Networks
TL;DR: The proposed application enables scalable wavelet-based compression, retrieval, and decompression of DICOM medical images and also supports ROI coding/decoding and the presented application is appropriate for use by mobile devices activating in heterogeneous radio settings.
Proceedings ArticleDOI
MultiWaveMed: a system for medical image retrieval through wavelets transformations
TL;DR: The focus of this paper is to show the utility of the wavelet transforms on medical image characterization and their suitability for image indexing and retrieval.
Journal ArticleDOI
Radiomics as a Quantitative Imaging Biomarker: Practical Considerations and the Current Standpoint in Neuro-oncologic Studies.
Ji Eun Park,Ho Sung Kim +1 more
TL;DR: The potential role of radiomics in oncologic studies, the basic analytic pipeline and special data handling with high-dimensional data to facilitate the radiomics approach as a tool for personalized medicine in on cancerology are described.
References
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Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Book
Ten lectures on wavelets
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
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Ten Lectures on Wavelets
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
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Orthonormal bases of compactly supported wavelets
TL;DR: This work construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity, by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction.
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Ideal spatial adaptation by wavelet shrinkage
TL;DR: In this article, the authors developed a spatially adaptive method, RiskShrink, which works by shrinkage of empirical wavelet coefficients, and achieved a performance within a factor log 2 n of the ideal performance of piecewise polynomial and variable-knot spline methods.