Barah payu dara iaitu barah paling biasa di kalangan wanita, tidak menunjukkan sebarang simptom pada peringkat awal. Oleh itu, ujian saringan awal adalah penting untuk mengesan penyakit ini pada peringkat awal yang seterusnya mampu mengurangkan kadar kematian. Walau bagaimanapun, ujian–ujian ini mempunyai limitasi dari segi imej payu dara yang diperoleh seperti kabur, gelap dan dipengaruhi hingar. Ini akan menutup kawasan tumor dan mikrokalsifikasi. Banyak teknik pemprosesan imej yang diperkenalkan untuk mengesan pinggir atau meruas morfologi barah payu dara ini. Ini termasuk algoritma pertumbuhan kawasan secara titik benih (SBRG). Walau bagaimanapun, 2 parameter iaitu titik benih dan nilai ambang algoritma SBRG perlu ditentukan secara manual oleh pengguna. Penyelidikan ini mencadangkan penentuan kedua–dua parameter ini secara automatik dengan melakukan pengubahsuaian terhadap algoritma SBRG. Algoritma yang dinamakan pertumbuhan kawasan secara titik benih terubahsuai (MSBRG) telah diuji ke atas imej mammogram dan ultra bunyi untuk mengesan tumor payu dara dan juga mikrokalsifikasi. Keputusan yang diperoleh menunjukkan bahawa teknik yang dicadangkan telah berjaya mengesan dan mengasingkan tumor dan mikrokalsifikasi daripada latar belakang dan hingar. Pinggir kawasan yang diperoleh oleh algoritma MSBRG adalah halus dan bersambung penuh. Ini memastikan bahawa saiz dan bentuk kawasan yang dikesan tidak terganggu. Ini mampu menolong doktor dalam proses pengesanan barah payu dara.
Kata kunci: Pertumbuhan kawasan secara titik benih terubahsuai, imej mammogram, imej ultra bunyi, mikrokalsifikasi, tumor payu dara
Breast cancer, a common female malignancy, does not show any symptoms in its early stage. Screening tests are therefore important to reduce the death rates. By far, mammography and ultrasound tests prove to be the tests for early detection of breast cancer. However, these tests have limitations such as blurriness, darkness and the existence of unwanted noise on the breast image, which can obscure breast tumours and microcalcifications; the salient features detected in cases of abnormality. Many image processing techniques have been introduced in order to detect the edges or segment these breast cancer morphologies including the seed based region growing (SBRG) algorithm. However, two parameters, namely the seed point and the threshold value of the conventional SBRG algorithm need to be determined manually. This paper attempts to automatically find these parameters by proposing the modified version of the SBRG algorithm. The proposed algorithm which is called the modified seed based region growing (MSBRG) algorithm has been tested on mammogram and ultrasound images to detect the breast tumour as well as microcalcification. The results show that the proposed method successfully detects and distinguish breast tumour and microcalcifications from the background and unwanted noises. The borders (edges) of regions found by the MSBRG algorithm are perfectly thin and connected. Hence, the size and shape of the regions will not be corrupted. These will certainly assist doctors in the breast cancer screening process.
Key words: Modified seed based region growing, mammogram images, ultrasound images, microcalcification, breast tumour
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