An image processing enhancement approach to extract information in gel electrophoresis image

Author(s):  
A.S. Kusim ◽  
N.E. Abdullah ◽  
A.A. Ab Rahim
2020 ◽  
pp. 1-15
Author(s):  
Rui Zhu ◽  
Mario V. Wüthrich

Abstract It has become of key interest in the insurance industry to understand and extract information from telematics car driving data. Telematics car driving data of individual car drivers can be summarised in so-called speed–acceleration heatmaps. The aim of this study is to cluster such speed–acceleration heatmaps to different categories by analysing similarities and differences in these heatmaps. Making use of local smoothness properties, we propose to process these heatmaps as RGB images. Clustering can then be achieved by involving supervised information via a transfer learning approach using the pre-trained AlexNet to extract discriminative features. The K-means algorithm is then applied on these extracted discriminative features for clustering. The experiment results in an improvement of heatmap clustering compared to classical approaches.


1984 ◽  
Vol 23 (01) ◽  
pp. 4-8
Author(s):  
U. Engelmann ◽  
H. P. Meinzer

SummaryIn medical and biological research considerable information is gained with regard to the molecular weight and the purity of samples with the aid of Polyacrylamid (PAGE) or agarose gel electrophoresis (AGE). The resulting gel images are usually evaluated by the scientists manually.Here we want to present procedures permitting an analysis of the images with the computer. The given tasks were solved using the interpreter PIC. PIC is an image processing system developed at the German Cancer Research Center. The latter was extended by special routines in the form of new commands, thus creating a modular, easy-to-use system.


2017 ◽  
Vol 5 (3) ◽  
pp. 223-237
Author(s):  
Arthi C ◽  
Savithri

Functional magnetic resonance imaging has become a very popular tool in neurological and medical analysis over the years.  According to collated data, in the year 1993, as few as 20 papers were presented on the topic of fmri analysis; However, a decade later, as many as 1800 research papers talk about fmri analysis – an exponential increase. An analysis of the activated regions within the brain can be used to detect the its reactions to various stimuli with greater confidence compared to other methods but the success of accurately identifying brain stimuli however lies in the efficiency of the image processing algorithms applied to extract information from the fMRI scans. This paper analyzes the effectiveness of commonly used image processing algorithms in fMRI studies by statistically analyzing their effectiveness in extracting ROI’s in various images (sample size = 17) and tries to project the efficiency of these systems in fMRI scanning.


Author(s):  
C.M.R. Caridade ◽  
A.R.S. Marcal ◽  
T. Mendonca ◽  
A.M. Pessoa ◽  
S. Pereira

BMC Genomics ◽  
2015 ◽  
Vol 16 (Suppl 12) ◽  
pp. S15 ◽  
Author(s):  
Apichart Intarapanich ◽  
Saowaluck Kaewkamnerd ◽  
Philip J Shaw ◽  
Kittipat Ukosakit ◽  
Somvong Tragoonrung ◽  
...  

2009 ◽  
Vol 96 (2) ◽  
pp. 188-195 ◽  
Author(s):  
M. Daszykowski ◽  
E. Mosleth Færgestad ◽  
H. Grove ◽  
H. Martens ◽  
B. Walczak

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