The objective concerning this study is to improve the veracity of brain carcinoma diagnosis and segmentation, accompanying the aim of aiding physicians in labeling specific brain tumors. Brain tumors are stable neoplasms within the brain. These tumors are caused by uncontrolled progress of abnormal containers. Classification of brain tumors is divided established the location of the carcinoma, the type of tissue produced, and either the tumor is diseased (malignant) or benign (favorable) and several additional considerations. In addition, a surgical biopsy of the doubtful tissue (cyst) is required to obtain more news about the type of tumor. Biopsy takes 10 to 15 days for lab testing. With the advantages of machine intelligence algorithms, especially the CNN procedure in classifying brain tumors and contour discovery, this research was conducted on the conduct of machine learning on MRI image results for sufferers with mind tumor using transfer knowledge EfficientNet-B7 and U-Net.
Author(s) Details:
Antonius Fajar Adinegoro,
Department of Physics, Udayana University, Bali,
Indonesia.
Gusti
Ngurah Sutapa,
Department
of Physics, Udayana University, Bali, Indonesia.
Anak Agung Ngurah Gunawan,
Department of Physics, Udayana University, Bali, Indonesia.
Ni Kadek Nova Anggarani,
Department of Physics, Udayana University, Bali, Indonesia.
Putu
Suardana,
Department of Physics, Udayana University, Bali,
Indonesia.
I.
Gde Antha Kasmawan,
Department
of Physics, Udayana University, Bali, Indonesia.
Please see the link here: https://stm.bookpi.org/RATMCS-V1/article/view/10689
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