A’ini, Lubna Nur (2016) Segmentasi Sel Kanker Payudara Pada Citra Mikroskopis Menggunakan Fuzzy Cmeans Dan Modifikasi Watershed. Undergraduate thesis, Institut Teknologi Sepuluh Nopember Surabaya.
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Abstract
Kanker payudara merupakan masalah besar di Indonesia maupun di negara lain. Citra mikroskopis sel kanker payudara memiliki beberapa macam karakteristik seperti warna, bentuk, ukuran, maupun tekstur yang menyebabkan segmentasi sulit dilakukan akibat terdapat sel bertumpuk. Tugas akhir ini mengimplementasikan algoritma Fuzzy CMeans dan modifikasi Watershed untuk memisahkan sel bertumpuk. Algoritma Fuzzy C-Means dan modifikasi Watershed mampu melakukan segmentasi dengan baik. Dari uji kinerja algoritma Fuzzy C-Means didapatkan rata-rata index ZSI sebesar 0.72 untuk citra Malignant dan 0.77 untuk citra Benignant. Adapun hasil pengujian pemisahan sel bertumpuk rata-rata akurasi tertinggi yang didapatkan yaitu 0.732 untuk citra Malignant dan 0.702 untuk citra Benignant
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Breast cancer is a major problem in Indonesia and in other countries. Microscopic image of breast cancer cells have a few different characteristics such as color, shape, size, or texture that causes segmentation are difficult to do because of overlapping cells. This final task implements Fuzzy C-Means Algorithm and Watershed modifications to separate the overlapping cells. Fuzzy C-Means Algorithm and Watershed modifications able to do segmentation well. From the Fuzzy C-Means Algorithm performance test, the average of the ZSI index is 0.72 for Malignant image and 0.77 for Benignant image. For the testing results of the overlapping cell separation, average of the highest accuracy is 0.732 for Malignant image and 0.702 for Benignant image
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA9.64 Fuzzy logic T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques |
| Divisions: | Faculty of Information Technology > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | EKO BUDI RAHARJO |
| Date Deposited: | 29 Apr 2020 04:00 |
| Last Modified: | 29 Apr 2020 04:00 |
| URI: | http://repository.its.ac.id/id/eprint/75888 |
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