ABSTRACT

Indo Intan, A Thyroid Carcinoma Histopatologic Pattern Recognition using the Adaptive Neural Fuzzy Inference System (ANFIS) Method (supervised by Zahir Zainuddin and Rhiza S. Sadjad ).

The main goal of this research is to create a pattern recognition system to identify 3 (three) types of thyroid carcinomas, namely (1) the papillary, (2) the follicular and (3) the anaplastic type of thyroid carcinomas.

As many as 170 samples have been taken from the Faculty of Medicine of Hasanuddin University and The General Hospital “Wahidin Sudirohusodo” laboratories in Makassar. A pattern recognition process using the Adaptive Neural Fuzzy Inference System (ANFIS) method is conducted to identify the types of samples by looking at the digital camera images of samples. The preparation of the pattern recognition process includes the image processing and feature extraction stages. The ANFIS method itself consists of the “learning” (or “training”) process and the recognition(or testing) process.  

In the first setting, 30 samples are taken as the training images and  the remainder 140 are used as the test images. The accuracy of the recognition is only 68,57% at the 400th iteration, and even decreases to 53,57% at the 800th iteration. The other setting uses 63 samples as the training images and the remainder 107 are used as the test images. The accuracy of the second setting turns out to be much better than the first one: 80,37% at the 400th iteration, but still decreases to 62,62% at the 800th iteration. The average recognition time at the 400th iteration is 21 seconds, twice as fast as the time at the 800th iteration, 40 seconds. Therefore, it is concluded that the system performs better at the 400th iteration as compared to the 800th iteration.