Clustered microcalcification classification using CC-MLO-view corresponding shape and distribution features

Conference proceedings article


ผู้เขียน/บรรณาธิการ


กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง


รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่งChiracharit W., Kongkachandra R.

ผู้เผยแพร่Hindawi

ปีที่เผยแพร่ (ค.ศ.)2008

หน้าแรก29

หน้าสุดท้าย34

จำนวนหน้า6

ISBN9784907764296

นอก0146-9428

eISSN1745-4557

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-56749174453&doi=10.1109%2fSICE.2008.4654617&partnerID=40&md5=5425cfdb9b9a2331373bc1a3845dcbbb

ภาษาEnglish-Great Britain (EN-GB)


ดูบนเว็บไซต์ของสำนักพิมพ์


บทคัดย่อ

Shape of single microcalcifications (μCa++s) and distribution of them in a cluster are two key features for a radiologist to diagnose this abnormality appearing on mammograms into benign type or malignant type of breast cancer. These two features from two-dimensional (2-D) mammogram image from two mammographic views, cranio-caudad view (CC) and medio-lateral oblique view (MLO), are inevitable conflicted because of lack of depth information. It makes a large contradictory information of the same microcalcification cluster in different view. This paper proposes to use threedimensional (3-D) shape and distribution features exacted from the view correspondence. To identify a 3-D position of microcalcificaitons, the candidate pairs in CC view and MLO view are stereo-matched based on their relative intensity and size. Occluded microcalcifications are separated by x-ray absorption property. The 3-D shape features are represented by their structural outline, spherical measurement, and thickness which are computed from Fourier descriptor of surface outlines, compactness and its intensity, respectively. The distribution feature is represented by 3-D cluster size, average distance between each microcalcifications, and cluster density. There are 12 features used as input features for three-layer feed-forward backpropagation neural network classifier which is constructed dynamically and weighted be training with forty benign and forty malignant microcalcificaitons. The evaluated performance of the proposed method is 96 percent sensitivity and 91 percent specificity. © 2008 SICE.


คำสำคัญ

breast cancerComputer-aided diagnosisMammogramMicrocalcificationStereo matching


อัพเดทล่าสุด 2023-04-10 ถึง 07:35