[HTML][HTML] Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks

JOB Diniz, PHB Diniz, TLA Valente, AC Silva… - Computer methods and …, 2018 - Elsevier
Abstract Background and Objective The processing of medical image is an important tool to
assist in minimizing the degree of uncertainty of the specialist, while providing specialists …

Deep learning based breast cancer detection and classification using fuzzy merging techniques

R Krithiga, P Geetha - Machine Vision and Applications, 2020 - Springer
Automatic identification of abnormal and normal cells is a critical step in computer-assisted
pathology, owing to certain heterogeneous characteristics of cancer cells. However …

Detection of masses in mammograms with adaption to breast density using genetic algorithm, phylogenetic trees, LBP and SVM

WB de Sampaio, AC Silva, AC de Paiva… - Expert Systems with …, 2015 - Elsevier
Breast cancer is the second commonest type of cancer in the world, and the commonest
among women, corresponding to 22% of the new cases every year. This work presents a …

Automatic detection of masses in mammograms using quality threshold clustering, correlogram function, and SVM

J de Nazaré Silva, AO de Carvalho Filho… - Journal of digital …, 2015 - Springer
Breast cancer is the second most common type of cancer in the world. Several computer-
aided detection and diagnosis systems have been used to assist health experts and to …

Automated segmentation of optic disc using statistical region merging and morphological operations

KS Nija, CP Anupama, VP Gopi, VS Anitha - Physical and Engineering …, 2020 - Springer
Abstract Accurate Optic Disc (OD) segmentation is vital in designing systems that aid the
diagnosis and evaluation of early phases of retinal diseases. However, in many images, the …

SRM superpixel merging framework for precise segmentation of cervical nucleus

R Saha, M Bajger, G Lee - 2019 Digital Image Computing …, 2019 - ieeexplore.ieee.org
Cervical nuclei contain important diagnostic characteristics useful for identifying abnormality
in cervical cells. Therefore, an accurate segmentation of nuclei is the primary step in …

3D segmentation for multi-organs in CT images

M Bajger, G Lee, M Caon - ELCVIA: electronic letters on computer vision …, 2013 - raco.cat
The study addresses the challenging problemof automatic segmentation of the human
anatomy needed for radiation dose calculations. Three-dimensional extensions of two well …

Computer-assisted segmentation of CT images by statistical region merging for the production of voxel models of anatomy for CT dosimetry

M Caon, J Sedlář, M Bajger, G Lee - Australasian Physical & Engineering …, 2014 - Springer
The segmentation of CT images to produce a computational model of anatomy is a time-
consuming and laborious process. Here we report a time saving semi-automatic approach …

[PDF][PDF] Multi-organ segmentation of CT images using statistical region merging

G Lee, M Bajger, M Caon - … Engineering (BioMed 2012): Proc. of the …, 2012 - academia.edu
Segmentation is one of the key steps in the process of developing anatomical models for
calculation of safe medical dose of radiation for children. This study explores the potential of …

Texture enhanced Statistical Region Merging with application to automatic knee bones segmentation from CT

M Howes, M Bajger, G Lee, F Bucci… - 2021 Digital Image …, 2021 - ieeexplore.ieee.org
Statistical Region Merging technique belongs to the portfolio of very successful image
segmentation methods across diverse domains and applications. The method is based on a …