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Detalhes

Detalhes

002
Publicações

2019

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

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

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

Abstract

2019

End-to-End Ovarian Structures Segmentation

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

Publicação
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

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

Publicação
Lecture Notes in Computer Science - Image Analysis and Recognition

Abstract

2019

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

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

Publicação
2019 IEEE International Ultrasonics Symposium (IUS)

Abstract

2018

3D mapping of choroidal thickness from OCT B-scans

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

Publicação
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.

Teses
supervisionadas

2019

Carotid Lumen Segmentation using a Neural Network Approach

Autor
Alexandre Saraiva Moreira

Instituição
UP-FEUP

2019

Pacient Validation Through Facial Recognition

Autor
Gustavo Fernando Marques Duarte de Faria

Instituição
UP-FEUP

2019

Segmentation and Quantification of Gynecological Structures from Ultrasound Images

Autor
Diego Santos Wanderley

Instituição
UP-FEUP

2017

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

Autor
Carlos Alexandre Nunes Ferreira

Instituição
UP-FEUP

2016

Estimation of choroidal thickness in OCT images

Autor
Simão Pedro Marques Pinto de Faria

Instituição
UP-FEUP