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Publications

Publications by Ana Maria Mendonça

2017

Automatic and semi-automatic approaches for arteriolar-to-venular computation in retinal photographs

Authors
Mendonca, AM; Remeseiro, B; Dashtbozorg, B; Campilho, A;

Publication
Medical Imaging 2017: Computer-Aided Diagnosis

Abstract

2014

Reliable Lung Segmentation Methodology by Including Juxtapleural Nodules

Authors
Novo, J; Rouco, J; Mendonca, A; Campilho, A;

Publication
IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT II

Abstract
In a lung nodule detection task, parenchyma segmentation is crucial to obtain the region of interest containing all the nodules. Thus, the challenge is to devise a methodology that includes all the lung nodules, particularly those close to the walls, as the juxtapleural nodules. In this paper, different region growing approaches are proposed for the automatic segmentation of the lung parenchyma. The methodology is organized in five different steps: first, the image intensity is corrected to improve the contrast of the lungs. With that, the fat area is obtained, automatically deriving the interior of the lung region. Then, the traquea is extracted by a 3D region growing, being subtracted from the lung region results. The next step is the division of the two lungs to guarantee that both are separated. And finally, the lung contours are refined to provide appropriate final results. The methodology was tested in 50 images taken from the LIDC image database, with a large variability and, specially, including different types of lung nodules. In particular, this dataset contains 158 nodules, from which 40 are juxtapleural nodules. Experimental results demonstrate that the method provides accurate lung regions, specially including the centers of 36 of the juxtapleural nodules. For the other 4, although the centers are not included, parts of their areas are retained in the segmentation, which is useful for lung nodule detection.

2015

Optic disc segmentation using the sliding band filter

Authors
Dashtbozorg, B; Mendonca, AM; Campilho, A;

Publication
COMPUTERS IN BIOLOGY AND MEDICINE

Abstract
Background: The optic disc (OD) centre and boundary are important landmarks in retinal images and are essential for automating the calculation of health biomarkers related with some prevalent systemic disorders, such as diabetes, hypertension, cerebrovascular and cardiovascular diseases. Methods: This paper presents an automatic approach for OD segmentation using a multiresolution sliding band filter (SBF). After the preprocessing phase, a low-resolution SBF is applied on a down-sampled retinal image and the locations of maximal filter response are used for focusing the analysis on a reduced region of interest (ROI). A high-resolution SBF is applied to obtain a set of pixels associated with the maximum response of the SBF, giving a coarse estimation of the OD boundary, which is regularized using a smoothing algorithm. Results: Our results are compared with manually extracted boundaries from public databases (ONHSD, MESSIDOR and INSPIRE-AVR datasets) outperforming recent approaches for OD segmentation. For the ONHSD, 44% of the results are classified as Excellent, while the remaining images are distributed between the Good (47%) and Fair (9%) categories. An average overlapping area of 83%, 89% and 85% is achieved for the images in ONHSD, MESSIDOR and INSPIR-AVR datasets, respectively, when comparing with the manually delineated OD regions. Discussion: The evaluation results on the images of three datasets demonstrate the better performance of the proposed method compared to recently published OD segmentation approaches and prove the independence of this method when from changes in image characteristics such as size, quality and camera field of view.

2013

An Automatic Method for the Estimation of Arteriolar-to-Venular Ratio in Retinal Images

Authors
Dashtbozorg, B; Mendonca, AM; Campilho, A;

Publication
2013 IEEE 26TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS)

Abstract
This paper presents an automatic approach for the estimation of Arteriolar-to-Venular Ratio (AVR) in retinal images. The method was assessed using the images of the INSPIRE-AVR database. A mean error of 0.05 was obtained when the method's results were compared with reference AVR values provided with this dataset, thus demonstrating the adequacy of the proposed solution for AVR estimation.

2013

Automatic Classification of Retinal Vessels Using Structural and Intensity Information

Authors
Dashtbozorg, B; Mendonca, AM; Campilho, A;

Publication
PATTERN RECOGNITION AND IMAGE ANALYSIS, IBPRIA 2013

Abstract
This paper presents an automatic approach for artery/vein (A/V) classification based on the analysis of a graph representing the structure of the retinal vasculature. The entire vascular tree is classified by deciding on the type of each intersection point (graph node) and assigning one of two classes to each vessel segment (graph link). The final label for each vessel segment is accomplished by a combination of structural information taken from the graph (link class) with intensity features measured in the original color image. An accuracy of 88.0% was achieved for the 40 images of the INSPIRE-AVR dataset, thus demonstrating that our method outperforms state-of-the-art approaches for A/V classification.

2013

Automatic Lane Segmentation in TLC Images Using the Continuous Wavelet Transform

Authors
Moreira, B; Sousa, A; Mendonca, AM; Campilho, A;

Publication
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE

Abstract
This paper describes a new methodology for lane detection in Thin-Layer Chromatography images. An approach based on the continuous wavelet transform is used to enhance the relevant lane information contained in the intensity profile obtained from image data projection. Lane detection proceeds in three phases: the first obtains a set of candidate lanes, which are validated or removed in the second phase; in the third phase, lane limits are calculated, and subtle lanes are recovered. The superior performance of the new solution was confirmed by a comparison with three other methodologies previously described in the literature.

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