Lymphoma Lesions Detection from Whole Body Diffusion-Weighted Magnetic Resonance Images
| Autor: | Mohamed Ali Cherni, Radhia Ferjaoui, Nour El Houda Kraiem, Tarek Kraiem |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Diffusion (acoustics)
medicine.diagnostic_test Lesion detection Computer science business.industry Magnetic resonance imaging Pattern recognition 02 engineering and technology Image segmentation Region growing algorithm medicine.disease 030218 nuclear medicine & medical imaging Lymphoma 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Sensitivity (control systems) Artificial intelligence Whole body business |
| Zdroj: | CoDIT |
| DOI: | 10.1109/codit.2018.8394840 |
| Popis: | Detecting lymphoma lesions in the whole body is tedious and so much time consuming. In this paper, we propose a semi-automatic lymphoma lesion detection based on Chan-Vese algorithm to help doctors in their diagnosis. In addition, this study will helps doctors in the ADC measurement of the lymph nodes. The proposed algorithm is applied on real DW-MRI images obtained from 1.5T MR scan. To evaluate the proposed method, we compared the obtained results with those obtained with the region growing algorithm (RG). This evaluation is basically based on: sensitivity, specificity, accuracy, precision, and recall. The obtained values for these parameters confirm the efficiency of the proposed method especially for the accuracy which reaches 99.94% with query times. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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