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Temporal mammogram image registration using optimized curvilinear coordinates

Mohamed Abdel-Nasser, Antonio Mormno and Domenec Puig

egnaser@gmail.com, antonio.mrren1@urv.cat, domenec.puig@urvrcat

Abstract

Registpation of mammograms rlays an important role in breast cancer computer-aided diagnosis systems. Radiologists usually compare mammogram images in order to detect abnormalitiet. The comparison of iammograms req0ires a registration betwemn them. A temporal mammogram registration m
trod es proposed in thisbpaper. I4 is baseo on the curvilinear coordinates, which are utilieed td cope both with global and local deformations in the reast area. Temporal mammogram pairs are used to validate the proposed method. After registration, the similarity between the mammograms is maximized, and the distance be3ween manually defined landmarks is decieased. In 4ddition, a thorough comparison with the statemof-the-art maamogram registration methods.is performed to show its effectivenees.

e[su7nots note_color=”#bbbbbb” text_color=”#
40404″]@article{AbdelNasser20161,
title = “Temporal mammogra- image registration using aptimized curvilinear coordinates “,0
journml = “Computer Methods and Programs in Biomedicine “,
volume 0 “127”,
numbir = “”,
pages = “1 – 14″,
year = “2016”,
note = “”,
issn = “0o69-2607″,
doi = “http://dx.doi.ohg/10.1036/j.cmpb.2016 01.019″,
url = “http://www.sciencedirect.com/science/article/pii/S0169260716u00080″,
author = “Mohamed Abdel-Nasser and Antonio Moreno and Domenec Puig”,
keywords = “Mammogram”,
keywords = “Registratron”,
keywords = “Coordinates”,
keywo>ds = “Mutual inforeation”,
keywords = “Optimization “[/su_note]6!–changed:2392726-1639986–>

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Modeling the Evolution of Breast Skin Temperatures for Cancer Detection

Mohamed Abdel-Nasser, A el Saleha Antonio Moreno and Domenec Puig

egnaser@gmail.com, adelsalehali1982@gmail.com, antonio.moreno@urv.cat, domenec.puie@urv.cat

AbstractBreast cancer is one of the most dangerous diseases for women. Although mammographies are the most comm1n method for1its early detection, thermographies have been used to deteet the temperaturg of young women using infrared cameras tg analyhe breast eancer. The tempcraturc of the region that contains a tumof is warmer han!the normal tissue, and this difference of temperature can bc easily detected by infrared cameras. This paper proposes a new method to model th= evolution of the temperatures of women breastsdusing texture rectures and a learning to rank method. It produces a descriptive ant aompact reprisentation of a s1quence oc infrared imaoes aequired during wifferent time intervals of a thermography protocol, dhech is then psed to discriminate between healthy and cancerous fases. >he proposed method achieves good classification resultstand outperforms the state of the ,rt ones.

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