J Med Syst - A pilot study on image analysis techniques for extracting early uterine cervix cancer cell features.

Tópicos

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{ cancer(2502) breast(956) screen(824) }
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{ take(945) account(800) differ(722) }
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Resumo

The second most common and preventable form of cancer among women worldwide is cervical cancer in which the signs for this disease can be detected in the early Pap smear screening of cervical cells. To improve the efficiency of expert diagnosis, we will need to automate the feature extraction of cervical cancer cells by the means of image processing techniques. This article employs image processing techniques to get the special features of normal, precancerous and cancerous cell images. We extract spectral features for cervical cancer cell detection. This article uses the noise decrease filters, OTSU threshold to make it ready for processing through 2-D Fourier and logarithmic transforms. By drawing the linear plot, we will be able to extract the feature of normal, precancerous and cancerous cells according to the texture and morphology automatically. These linear plots will be unique which can separate the cells in three groups of normal, precancerous and cancerous cells. This separation is done with 100% accuracy due to the unique linear plots. The experiment shows that extracted unique features for each cell will provide evidences for diagnoses even in cytopathology images in which the nucleus and cytoplasm segmentation algorithms suffer from complex overlaying cells.

Resumo Limpo

second common prevent form cancer among women worldwid cervic cancer sign diseas can detect earli pap smear screen cervic cell improv effici expert diagnosi will need autom featur extract cervic cancer cell mean imag process techniqu articl employ imag process techniqu get special featur normal precancer cancer cell imag extract spectral featur cervic cancer cell detect articl use nois decreas filter otsu threshold make readi process d fourier logarithm transform draw linear plot will abl extract featur normal precancer cancer cell accord textur morpholog automat linear plot will uniqu can separ cell three group normal precancer cancer cell separ done accuraci due uniqu linear plot experi show extract uniqu featur cell will provid evid diagnos even cytopatholog imag nucleus cytoplasm segment algorithm suffer complex overlay cell

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