Implementation of a faster R-CNN algorithm for identification of metastatic tissue using lymphoma histopathological images
نویسندگان
چکیده
Procedures for diagnosis of lymphoma includes blood tests, CT scan or MRI, and histopathological examination through a biopsy. Histopathological is the gold standard diagnosis. Pathology challenging difficult in field diagnostic pathology. This study aims to identify lymph node metastases using Faster R-CNN algorithm images nodes so that RCNN system design can help medical team make decisions. Identification carried out by classifying into normal classes metastatic classes. Loss values are not indicated underfitting overfitting shown from 10th epoch 20th epoch. The optimizer number epochs optimal value 83.3% accuracy 71.8% recall ADAM with 20 epochs. results obtained quite good. 1113 1478 were predicted correctly, while 437 82 incorrectly.
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ژورنال
عنوان ژورنال: Journal of Soft Computing Exploration
سال: 2023
ISSN: ['2746-0991', '2746-7686']
DOI: https://doi.org/10.52465/joscex.v4i2.144