Stability and Reproducibility of Radiomic Features Based Various Segmentation Technique on MR Images of Hepatocellular Carcinoma (HCC)

Hepatocellular carcinoma (HCC) is considered as a complex liver disease and ranked as the eighth-highest mortality rate with a prevalence of 2.4% in Malaysia. Magnetic resonance imaging (MRI) has been acknowledged for its advantages, a gold technique for diagnosing HCC, and yet the false-negative diagnosis from the examinations is inevitable. In this study, 30 MR images from patients diagnosed with HCC is used to evaluate the robustness of semi-automatic segmentation using the flood fill algorithm for quantitative features extraction. The relevant features were extracted from the segmented MR images of HCC. Four types of features extraction were used for this study, which are tumour intensity, shape feature, textural feature and wavelet feature. A total of 662 radiomic features were extracted from manual and semi-automatic segmentation and compared using intra-class relation coefficient (ICC). Radiomic features extracted using semi-automatic segmentation utilized flood filling algorithm from 3D-slicer had significantly higher reproducibility (average ICC = 0.952 ± 0.009, p < 0.05) compared with features extracted from manual segmentation (average ICC = 0.897 ± 0.011, p > 0.05). Moreover, features extracted from semi-automatic segmentation were more robust compared to manual segmentation. This study shows that semi-automatic segmentation from 3D-Slicer is a better alternative to the manual segmentation, as they can produce more robust and reproducible radiomic features.

Phase-field model of precipitation processes with coherency loss

A phase-field model is proposed to simulate coherency loss coupled with microstructure evolution. A special field variable is employed to describe the degree of coherency loss of each particle and its evolution is governed by a Ginzburg-Landau type kinetic equation. For the sake of computational efficiency, a flood-fill algorithm is introduced that can drastically reduce the required number of field variables, which allows the model to efficiently simulate a large number of particles sufficient for characterizing their statistical features during Ostwald ripening. The model can incorporate size dependence of coherency loss, metastability of coherent particles, and effectively incorporate the underlying mechanisms of coherency loss by introducing a so-called differential energy criterion. The model is applied to simulate coarsening of Al3Sc precipitates in aluminum alloy and comprehensively compared with experiments. Our results clearly show how the particle size distribution is changed during coherency loss and affects the coarsening rate.

PERANCANGAN GAME EDUKASI SEBAGAI MEDIA PEMBELAJARAN BERBASIS MOBILE MENGGUNAKAN ALGORITMA FISHER-YATES DAN FLOOD FILL

<p><em>Information technology is currently increasingly developing, especially on smartphone devices. The reason various users use smartphone devices is their practical size and of course their portability. Smartphone devices can also be a learning medium in the form of games or games, one of which is games for children's education. The problem that often occurs in children in the way of learning is that it is easy to develop boredom if the child is only encouraged by learning material without any entertainment or games. This game is designed to change the way of learning, especially in early childhood between the ages of 3 to 6 years. This mobile-based game is made using the App Inventor with an interactive and attractive display to learn to recognize numbers, fruit, letters, animals, vegetables and colors as well as quiz questions. In this educational game that was made, it was designed using the Rapid Application Development (RAD) method as a completion stage starting from the planning stage to the implementation stage of the program. This educational game also applies the Fisher-Yates algorithm to randomize questions. The results of this study show 10 quiz questions randomly from 15 existing questions, and apply the Flood Fill algorithm for coloring objects or images. With the design of games for mobile-based education, it is hoped that it can make children's brains more active and creative during their growth period and help children's learning processes in order to increase their broader knowledge.</em></p><p><strong><em>Keyword: </em></strong><em>App Inventor, Fisher Yates, Flood Fill, Education Game, RAD</em><em> </em></p><p><em>Teknologi informasi pada saat ini semakin hari semakin berkembang, khususnya pada perangkat smartphone. Alasan dari berbagai pengguna menggunakan perangkat smartphone adalah ukurannya yang praktis dan tentunya mudah dibawa. Perangkat smartphone juga bisa menjadi media pembelajaran dalam bentuk permainan atau game, salah satunya adanya game untuk edukasi anak. Permasalahan yang kerap terjadi pada anak dalam cara belajar yaitu mudah timbulnya kebosanan jika anak hanya didorongkan oleh materi pembelajaran saja tanpa adanya hiburan atau permainan. Dirancangnya game ini untuk mengubah cara belajar khususnya pada anak usia dini antara umur 3 sampai 6 tahun. Pada game berbasis mobile ini dibuat menggunakan App Inventor dengan tampilan yang interaktif dan menarik untuk belajar mengenal angka, buah, huruf, hewan, sayur dan warna serta adanya soal kuis. Pada game edukasi ini yang dibuat ini dirancang menggunakan metode Rapid Application Development (RAD) sebagai tahapan penyelesaian mulai dari tahap perencanaan sampai tahap implementasi dari program. Pada game edukasi ini juga menerapkan algoritma Fisher-Yates untuk melakukan pengacakan soal. Pada hasil penelitian ini ditampilkan 10 soal kuis secara acak dari 15 soal yang ada, serta menerapkan algoritma Flood Fill untuk pewarnaan objek atau gambar. Dengan dirancangnya game untuk edukasi berbasis mobile ini diharapkan dapat membuat otak anak lebih aktif dan kreatif dimasa pertumbuhannya serta membantu proses belajar anak agar dapat menambah pengetahuan yang lebih luas.</em></p><p><strong><em>Kata kunci:</em></strong><em> App Inventor, Fisher Yates, Flood Fill, Game Edukasi, RAD</em></p>

Extracting a Bounded Region from a Map Using Flood Fill Algorithm

Extracting the needed portion from a bounded region is an important task in image processing. Editing a map and extracting a region from the map is challenging. It is useful in some contexts to have a region in a separate sheet. In this image processing, we have used the Flood Fill algorithm to extract a region from the image map. To achieve that goal, we had worked in our study to separate a bounded region on a map. Usually, a scanned map may contain a lot of useless information. So we have to process the image to remove useless information from the map. We had quantized the image to a binary one. In the second phase, we have applied a gray color to separate the desired position from a map. Our main objective of the study to extract a bounded region from mapping an image that contains useless information and removes it. We have experimented with several maps and it works successfully.