Hyperchromasia and Texture as effective features for analysis of malignancy in Pap smear Images

نویسندگان

  • Lipi B Mahanta
  • Kangkana Bora
چکیده

This work presents an approach for the analysis of abnormality in the cervical cells based on Texture and presence of Hyperchromasia, which are two important morphological features based on which one can distinguish between normal and abnormal cervical cells. The proposed approach is implemented in MATLAB®, a high level, interactive environment for data visualization/analysis/computation. This may help pathologist in identification of cervical cancer from Pap smear images and help in early diagnosis.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Does Multispectral Texture Features Really Improve Cervical Cancer Detection?

For cervical cancer detection, the performance of multispectral texture (MST) features extracted from multispectral Pap smear images is evaluated. In this study we carried out pairwise comparisons between different image features, including MST versus average spectral texture features (AST, without spectral information), and MST versus multispectral intensity features (MSI, without texture info...

متن کامل

Robust and Efficient Diagnosis of Cervical Cancer in Pap Smear Images Using Textures Features with Rbf and Kernel Svm Classification

Classification of medical imagery is a difficult and challenging process due to the intricacy of the images and lack of models of the anatomy that totally captures the probable distortions in each structure. Cervical cancer is one of the major causes of death among other types of the cancers in women worldwide. Proper and timely diagnosis can prevent the life to some level. Consequently we have...

متن کامل

Improvement of Multi Layer Perceptron Classification on Cervical Pap smear data with Feature Extraction

Artificial Neural Network (ANN) is an effective technique of Soft Computing can model ComputerAided Diagnosis (CAD) system efficiently. CAD system is an essential for the prediction of Malignancy in Cervical Cancer. Cervical Cancer can be cured if it is diagnosed in early stages. Hence, for the effective screening of cancer lesions in the Cervical cell images which are captured using Pap smear ...

متن کامل

Scale - Space Texture Analysis

In this paper we propose a technique for classifying images by modeling features extracted at di erent scales. Speci cally, we use texture measures derived from Pap smear cell nuclei images using a Grey Level Co-occurrence Matrix (GLCM). For a texture feature extracted from the GLCM at a number of distances we hypothesise that by modeling the feature as a continuous function of scale we can obt...

متن کامل

Nominated Texture Based Cervical Cancer Classification

Accurate classification of Pap smear images becomes the challenging task in medical image processing. This can be improved in two ways. One way is by selecting suitable well defined specific features and the other is by selecting the best classifier. This paper presents a nominated texture based cervical cancer (NTCC) classification system which classifies the Pap smear images into any one of t...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013