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Detection of prostate cancer in multiparametric MRI using random forest with instance weighting
A prostate computer-aided diagnosis (CAD) based on random forest to detect prostate cancer using a combination of spatial, intensity, and texture features extracted from three sequences, T2W, ADC, and B2000 images, is proposed. The random forest training considers instance-level weighting for equal...
שמור ב:
| הוצא לאור ב: | J Med Imaging (Bellingham) |
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| Main Authors: | , , , , , , , , |
| פורמט: | Artigo |
| שפה: | Inglês |
| יצא לאור: |
Society of Photo-Optical Instrumentation Engineers
2017
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| נושאים: | |
| גישה מקוונת: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5467765/ https://ncbi.nlm.nih.gov/pubmed/28630883 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.4.2.024506 |
| תגים: |
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