2007
DOI: 10.2349/biij.3.1.e9
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Increasing the speed of medical image processing in MatLab®

Abstract: MatLab® has often been considered an excellent environment for fast algorithm development but is generally perceived as slow and hence not fit for routine medical image processing, where large data sets are now available e.g., high-resolution CT image sets with typically hundreds of 512x512 slices. Yet, with proper programming practices – vectorization, pre-allocation and specialization – applications in MatLab® can run as fast as in C language. In this article, this point is illustrated with fast implementati… Show more

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Cited by 16 publications
(12 citation statements)
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“…Images at the middle thigh level were analyzed in a semiautomatic approach using ImageJ and custom-written code in Matlab, version 7.14.0.0739 (R2012a). 25 , 26 A total number of 2400 images were analyzed accordingly. Anatomical segmentation of the sciatic nerve’s tibial compartment and the proximal tibial nerve was performed for all participants.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Images at the middle thigh level were analyzed in a semiautomatic approach using ImageJ and custom-written code in Matlab, version 7.14.0.0739 (R2012a). 25 , 26 A total number of 2400 images were analyzed accordingly. Anatomical segmentation of the sciatic nerve’s tibial compartment and the proximal tibial nerve was performed for all participants.…”
Section: Methodsmentioning
confidence: 99%
“…The detailed process of anatomical nerve segmentation and lesion mapping has been described elsewhere. 10 Binarized maps of lesions and vital nerve tissue were analyzed in Matlab 26 (Figure 1B-D gives a 3-dimensional reconstruction of T2wFS-hypointense tibial nerve lesions in 3 patients with T2D at different clinical stages of DPN). Specifically, we determined the lesion ratio as the number of lesion voxels divided by the number of voxels in vital nerve tissue.…”
Section: Methodsmentioning
confidence: 99%
“…All images were collected using phase contrast optics on an Olympus IX‐81 microscope (Olympus America Inc., Melville, NY) using a 20× objective and videos were recorded at 72 frames/s. Image processing was done via MATLAB (The MathWorks, Natick, MA) (Bister, 2007; Zuria et al, 1998) and statistical analysis was computed in Origin (OriginLab Corporation, Northhamption, MA). To track the myocyte contraction, we introduce the DMG.…”
Section: Methodsmentioning
confidence: 99%
“…In recent years, Matlab, the product of MathWorks, has become a popular tool for fast development. Its many Toolboxes, powerful interface and user friendliness make it a tool of choice in many disciplines, including medical image processing [13]. The toolbox functions implemented in the open MATLAB language can be used to develop the customized algorithms [14].…”
Section: Matlabmentioning
confidence: 99%