A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
Filters
Applying spatial distribution analysis techniques to classification of 3D medical images
2005
Artificial Intelligence in Medicine
Preserved Fulltext
The later technique could still be a method of choice when the distributions differ significantly, since it is faster and less complex. ...
Conclusion: Performed experiments demonstrated that the approaches based on the KL divergence and the ML method provide superior accuracy compared to the Mahalanobis distance. ...
In addition, the authors express their gratitude to the anonymous reviewers whose comments significantly improved the structure and overall quality of the paper. ...
doi:10.1016/j.artmed.2004.07.001
pmid:15811790
fatcat:64ysxglcyrby7glgn4he5rhbcu
Subjective probability
[chapter]
2008
Nonbayesian Decision Theory
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
The later technique could still be a method of choice when the distributions differ significantly, since it is faster and less complex. ...
Conclusion: Performed experiments demonstrated that the approaches based on the KL divergence and the ML method provide superior accuracy compared to the Mahalanobis distance. ...
In addition, the authors express their gratitude to the anonymous reviewers whose comments significantly improved the structure and overall quality of the paper. ...
doi:10.1007/978-1-4020-8699-1_6
fatcat:wsmau6v4nndd5euqqzrovedkbi
Subjective Probability
1957
Nature
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
The later technique could still be a method of choice when the distributions differ significantly, since it is faster and less complex. ...
Conclusion: Performed experiments demonstrated that the approaches based on the KL divergence and the ML method provide superior accuracy compared to the Mahalanobis distance. ...
In addition, the authors express their gratitude to the anonymous reviewers whose comments significantly improved the structure and overall quality of the paper. ...
doi:10.1038/180158a0
fatcat:m7uekfmtb5echej5wccoio4ide
An adaptive partitioning approach for mining discriminant regions in 3D image data
2007
Journal of Intelligent Information Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Mining discriminative spatial patterns in image data is an emerging subject of interest in medical imaging, meteorology, engineering, biology, and other fields. ...
In this paper, we propose a novel approach for detecting spatial regions that are highly discriminative among different classes of three dimensional (3D) image data. ...
Acknowledgements The authors would like to thank A. Saykin for providing the fMRI dataset and clinical expertise. ...
doi:10.1007/s10844-007-0043-2
fatcat:w4t4zt5n75b3vjnvjf7urbcjui
Computationally Intelligent Methods for Mining 3D Medical Images
[chapter]
2004
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2006; you can also visit the original URL.
The file type is application/pdf.
We present novel intelligent tools for mining 3D medical images. ...
We apply quantitative characterization techniques to extract k-dimensional signatures from the highly discriminative ROIs. Finally, we use neural networks for classification. ...
Acknowledgement The authors would like to thank A. Saykin for providing the fMRI data set and clinical expertise and J. Ford for performing some of the preprocessing of this data set. ...
doi:10.1007/978-3-540-24674-9_9
fatcat:f44lzhgo2bcflay4fg7rtc376u
Fast and effective characterization of 3D region of interest in medical image data
2004
Medical Imaging 2004: Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2005; you can also visit the original URL.
The file type is application/pdf.
A necessary step prior to classification is efficient extraction of discriminative features. For this purpose, we apply a characterization technique especially designed for spatial ROIs. ...
The main idea of this technique is to extract a k-dimensional feature vector using concentric spheres in 3D (or circles in 2D) radiating out of the ROIís center of mass. ...
ACKNOWLEDGEMENT The authors would like to thank A. Saykin for providing the fMRI data set and clinical expertise and J. Ford for performing some of the preprocessing of this data set. ...
doi:10.1117/12.534459
dblp:conf/miip/KontosM04
fatcat:vza5lcpyfvbh7ettulm6gsjuqi
A Multi-Volume Visualization Framework for Spatial Aligned Volumes after 3D/3D Image Registration
2009
2009 First International Conference on Information Science and Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2012; you can also visit the original URL.
The file type is application/pdf.
A new method for the visualization of spatial aligned volumes after 3D/3D image registration is presented in this paper. ...
Then, a statistical vectorial volume classification method based on neighborhood weighted Gaussian mixture model is applied to analyze the vectorial volume and get material distribution information. ...
Conclusions With the development of 3D/3D medical image registration methods, more and more application meets the requirement of the visualization of spatial-aligned volumes. ...
doi:10.1109/icise.2009.77
fatcat:fg3gkq76pbg7vlkqpuftd7vyea
Information Extraction Techniques in Hyperspectral Imaging Biomedical Applications
[chapter]
2020
Multimedia Information Retrieval [Working Title]
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
One of the most relevant challenges in medical HSI is the information extraction, where image processing methods are used to extract useful information for disease detection and diagnosis. ...
Hyperspectral imaging (HSI) is a technology able to measure information about the spectral reflectance or transmission of light from the surface. ...
Conflict of interest The authors declare that there are no conflicts of interest related to this chapter. © 2020 The Author(s). Licensee IntechOpen. ...
doi:10.5772/intechopen.93960
fatcat:beqkyox6mzhwpg62ncjj2je3ki
Fast and effective characterization for classification and similarity searches of 2D and 3D spatial region data
2005
Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Similarity searches on artificial data demonstrate that our technique, although straightforward, compares favorably to mathematical morphology, while being two orders of magnitude faster. ...
The method efficiently constructs a kdimensional feature vector using concentric spheres in 3D (circles in 2D) radiating out of a region's center of mass. ...
Acknowledgements The authors would like to thank A. Saykin for providing the fMRI data set and clinical expertise, J. Ford for performing part of the preprocessing of this dataset, and H. ...
doi:10.1016/j.patcog.2005.04.020
pmid:16565747
pmcid:PMC1413499
fatcat:7fvqdlad6vh6zngrqg2rt2hide
3D Medical Volume Segmentation Using Hybrid Multiresolution Statistical Approaches
2010
Advances in Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Multiresolution Analysis (MRA) enables the preservation of an image according to certain levels of resolution or blurring. ...
This paper focuses on the implementation of efficient medical volume segmentation techniques. ...
Many feature selection techniques have been tested in medical images, and the best results were achieved using the grey-scale values of the medical image pixels to generate the probability distribution ...
doi:10.1155/2010/520427
fatcat:y47agikf3nasvck2rgvuggn66q
Extraction of Discriminative Functional MRI Activation Patterns and an Application to Alzheimer's Disease
[chapter]
2004
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The goal is to efficiently identify spatial regions that are associated with non-spatial variables through adaptive recursive partitioning of the 3D space into a number of hyperrectangles utilizing statistical ...
Given: Oct-tree T corresponding to the spatial domain D; Two sets S Y = {S 1,Y ,...S n1,Y }, S N = {S 1,N ,...S n2,N } containing region data for samples belonging to classes Y and N respectively. ...
Some initial attempts to apply the technique on brain images have been reported in [10] . ...
doi:10.1007/978-3-540-30136-3_89
fatcat:ifptjikrkbdoba44xxpimjbahq
Intelligent Techniques in Medical Volume Visualization
2015
Procedia Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The past few decades have witnessed an increasing number of new techniques being developed for practical clinical image display. ...
This paper presents the recent intelligent techniques and algorithms used for medical data visualization. These techniques cover filtering, segmentation, classification and visualization. ...
•Does not utilise spatial information.
Medical Image Classification Techniques Mapping images into predefine classes is called image classification. ...
doi:10.1016/j.procs.2015.09.129
fatcat:4hmfq2jowffe5jxqzrfkhsnwm4
The Usage of Modern Data Science in Segmentation and Classification: Machine Learning and Microscopy
2017
Microscopy and Microanalysis
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
While these technologies have transformed many areas of data science ranging from medical diagnosis to stock market analysis, frequently image analysis for microscopy (outside some specific areas of application ...
These higher dimensional spaces may be (spatially and / or temporally correlated) images acquired in different imaging modalities (i.e. using different detectors, energies or techniques to extract different ...
While these technologies have transformed many areas of data science ranging from medical diagnosis to stock market analysis, frequently image analysis for microscopy (outside some specific areas of application ...
doi:10.1017/s1431927617001465
fatcat:wyuggtewuvdulhcx2osx5dolbm
Applying 3D U-Net Architecture to the Task of Multi-Organ Segmentation in Computed Tomography
2020
Applied Computer Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
AbstractThe achievement of high-precision segmentation in medical image analysis has been an active direction of research over the past decade. ...
Convolutional architectures have been mostly applied to homogeneous medical datasets with separate organs. ...
This technique, called "supervised learning", has enhanced biomedical and radiological visualisation [5] , and significantly refined leading-edge approaches in medical image analysis [6] . ...
doi:10.2478/acss-2020-0005
fatcat:e77qbkxn4ncw5pahmujzwrttma
A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis
2020
Frontiers in Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Deep learning has recently been used for the analysis of neuroimages, such as structural magnetic resonance imaging (MRI), functional MRI, and positron emission tomography (PET), and it has achieved significant ...
We first provide a comprehensive overview of deep learning techniques and popular network architectures by introducing various types of deep neural networks and recent developments. ...
The classification is one of the first tasks in which deep learning giving a major contribution to medical image analysis. This task aims to classify medical images into two or more classes. ...
doi:10.3389/fnins.2020.00779
pmid:33117114
pmcid:PMC7578242
fatcat:tzdcq3kyyrefvn7vxgdj5lnhju
« Previous
Showing results 1 — 15 out of 26,510 results