By Alan http://alanpeng.wang
The segmentation of ultrasonic images of breast tumors is very important for medical diagnosis and artificial intelligence landing on medical images. In this repository, four different tumor segmentation models have been implemented based on previous studies, and the advantages and disadvantages of these models have been analyzed from the four aspects of segmentation effect, operation rate, pretreatment effect and generalization ability, which can help readers quickly understand the difficulties in ultrasonic image segmentation of breast tumors and the advantages and disadvantages of some algorithms.
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Firstly, you should download all the files or download the Matlab library support from https://www.tamps.cinvestav.mx/~wgomez/downloads.html.
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Secondly, as the hint says, you are supposed to run the RUN_ME_FIRST.m first.
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Thirdly, as you can see, the folder Experiments contains four folders and each folder contains one model. You can run the example(i) to test the model. Before you run, please check to add all the path or you will need to recreate the lacking .m file.
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Lastly, you can refer to the folder Reports if you still have something that you don't understand.
We would like to acknowledge Arturo Rodríguez-Cristerna, Wilfrido Gómez-Flores, and Wagner Coelho de Albuquerque-Pereira, ''BUSAT: A MATLAB Toolbox for Breast Ultrasound Image Analysis'', In: 9th Mexican Congress on Pattern Recognition (MCPR 2017), LNCS 10267, pp. 268-277, 2017. DOI: 10.1007/978-3-319-59226-8_26.