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002
Publications

2019

Quantitative Assessment of Central Serous Chorioretinopathy in Angiographic Sequences of Retinal Images

Authors
Ferreira, CA; Penas, S; Silva, J; Mendonca, AM;

Publication
2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG)

Abstract

2019

End-to-End Ovarian Structures Segmentation

Authors
Wanderley, DS; Carvalho, CB; Domingues, A; Peixoto, C; Pignatelli, D; Beires, J; Silva, J; Campilho, A;

Publication
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - Lecture Notes in Computer Science

Abstract

2019

Deep Learning Approaches for Gynaecological Ultrasound Image Segmentation: A Radio-Frequency vs B-mode Comparison

Authors
Carvalho, C; Marques, S; Peixoto, C; Pignatelli, D; Beires, J; Silva, J; Campilho, A;

Publication
Lecture Notes in Computer Science - Image Analysis and Recognition

Abstract

2019

Segmentation of gynaecological ultrasound images using different U-Net based approaches

Authors
Marques, S; Carvalho, C; Peixoto, C; Pignatelli, D; Beires, J; Silva, J; Campilho, A;

Publication
2019 IEEE International Ultrasonics Symposium (IUS)

Abstract

2018

3D mapping of choroidal thickness from OCT B-scans

Authors
Faria, SP; Penas, S; Mendonca, L; Silva, JA; Mendonca, AM;

Publication
Lecture Notes in Computational Vision and Biomechanics

Abstract
The choroid is the middle layer of the eye globe located between the retina and the sclera. It is proven that choroidal thickness is a sign of multiple eye diseases. Optical Coherence Tomography (OCT) is an imaging technique that allows the visualization of tomographic images of near surface tissues like those in the eye globe. The automatic calculation of the choroidal thickness reduces the subjectivity of manual image analysis as well as the time of large scale measurements. In this paper, a method for the automatic estimation of the choroidal thickness from OCT images is presented. The pre-processing of the images is focused on noise reduction, shadow removal and contrast adjustment. The inner and outer boundaries of the choroid are delineated sequentially, resorting to a minimum path algorithm supported by new dedicated cost matrices. The choroidal thickness is given by the distance between the two boundaries. The data are then interpolated and mapped to an infrared image of the eye fundus. The method was evaluated by calculating the error as the distance from the automatically estimated boundaries to the boundaries delineated by an ophthalmologist. The error of the automatic segmentation was low and comparable to the differences between manual segmentations from different ophthalmologists. © 2018, Springer International Publishing AG.

Supervised
thesis

2017

Quantitative assessment of Central Serous Chorioretinopathy in Angiographic sequences of retinal images

Author
Carlos Alexandre Nunes Ferreira

Institution
UP-FEUP

2016

Estimation of choroidal thickness in OCT images

Author
Simão Pedro Marques Pinto de Faria

Institution
UP-FEUP

2015

3D reconstruction from multiple RGB-D images with different perspectives

Author
Mário André Pinto Ferraz de Aguiar

Institution
UP-FEUP