Robust Breast cancer Detection using Faster R-CNN Algorithm
Dublin Core
Title
Robust Breast cancer Detection using Faster R-CNN Algorithm
Subject
Breast Cancer Detection, Deep Learning, Faster R-CNN
Description
One of the most common screening tools for breast cancer detection is ultrasound. However, the lack of qualified radiologists causes the diagnosis process to become a challenging task. Deep learning's promising achievement in various computer vision problems inspires us to apply the technology to medical image recognition problems. We propose a detection model based on the Faster R-CNN to detect breast cancer quickly and accurately. We conduct this experiment by collecting breast cancer datasets, conducting pre-processing, training models, and evaluating the model performance. Based on the experiment result, we obtainthat this model can detect breast cancer with bounding boxes. In this model, it is possible to detect the bounding box that is more than what it should be, so we applied NMS to eliminate the prediction of the bounding box that is less precise to increase accuracy
Creator
Anisa Dian Pratiwi1, Irma Permata Sari
Source
https://ijicom.respati.ac.id/index.php/ijicom/article/view/49/36
Date
August 2022
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Anisa Dian Pratiwi1, Irma Permata Sari, “Robust Breast cancer Detection using Faster R-CNN Algorithm,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8377.