Classification of Micro-calcification in Mammograms using Scalable Linear Fisher Discriminant Analysis

Zobia Suhail, Erika R. E. Denton, Reyer Zwiggelaar

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

25 Dyfyniadau(SciVal)
139 Wedi eu Llwytho i Lawr (Pure)


Breast cancer is one of the major causes of death in women. Computer Aided Diagnosis (CAD) systems are being developed to assist radiologists in early diagnosis. Microcalcifications can be an early symptom of breast cancer. Besides detection, classification of micro-calcification as benign or malignant is essential in a complete CAD system.We have developed a novel method for the classification of benign and malignant microcalcification using an improved Fisher Linear Discriminant Analysis (LDA) approach for the linear transformation of segmented micro-calcification data in combination with a Support Vector Machine (SVM) variant to classify between the two classes. The results indicate an average accuracy equal to 96% which is comparable to state-of-the art methods in the literature.
Iaith wreiddiolSaesneg
Tudalennau (o-i)1475-1485
Nifer y tudalennau11
CyfnodolynMedical and Biological Engineering and Computing
Rhif cyhoeddi8
Dyddiad ar-lein cynnar25 Ion 2018
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 01 Awst 2018

Ôl bys

Gweld gwybodaeth am bynciau ymchwil 'Classification of Micro-calcification in Mammograms using Scalable Linear Fisher Discriminant Analysis'. Gyda’i gilydd, maen nhw’n ffurfio ôl bys unigryw.

Dyfynnu hyn