Search Results for author: Joao F. C. Mota

Found 8 papers, 3 papers with code

Towards Tumour Graph Learning for Survival Prediction in Head & Neck Cancer Patients

no code implementations17 Apr 2023 Angel Victor Juanco Muller, Joao F. C. Mota, Keith A. Goatman, Corne Hoogendoorn

First, the scans with arbitrary FoV are cropped to the head and neck region and a u-shaped convolutional neural network (CNN) is trained to segment the region of interest.

Decision Making Graph Learning +3

The Topology-Overlap Trade-Off in Retinal Arteriole-Venule Segmentation

no code implementations31 Mar 2023 Angel Victor Juanco Muller, Joao F. C. Mota, Keith A. Goatman, Corne Hoogendoorn

However, we show that by including an orientation score guided convolutional module, based on the anisotropic single sided cake wavelet, we reduce such misclassification and further increase the topology correctness of the results.

Sharper Bounds for Proximal Gradient Algorithms with Errors

no code implementations4 Mar 2022 Anis Hamadouche, Yun Wu, Andrew M. Wallace, Joao F. C. Mota

We analyse the convergence of the proximal gradient algorithm for convex composite problems in the presence of gradient and proximal computational inaccuracies.

Image-Guided Depth Upsampling via Hessian and TV Priors

no code implementations31 Oct 2019 Alireza Ahrabian, Joao F. C. Mota, Andrew M. Wallace

We propose a method that combines sparse depth (LiDAR) measurements with an intensity image and to produce a dense high-resolution depth image.

Coupled Dictionary Learning for Multi-contrast MRI Reconstruction

1 code implementation26 Jun 2018 Pingfan Song, Lior Weizman, Joao F. C. Mota, Yonina C. Eldar, Miguel R. D. Rodrigues

In this paper, we propose a Coupled Dictionary Learning based multi-contrast MRI reconstruction (CDLMRI) approach to leverage an available guidance contrast to restore the target contrast.

Anatomy Denoising +2

Multi-modal dictionary learning for image separation with application in art investigation

no code implementations14 Jul 2016 Nikos Deligiannis, Joao F. C. Mota, Bruno Cornelis, Miguel R. D. Rodrigues, Ingrid Daubechies

Our dictionary learning framework can be tailored both to a single- and a multi-scale framework, with the latter leading to a significant performance improvement.

Dictionary Learning

Compressed Sensing with Prior Information: Optimal Strategies, Geometry, and Bounds

2 code implementations22 Aug 2014 Joao F. C. Mota, Nikos Deligiannis, Miguel R. D. Rodrigues

Our bounds and geometrical interpretations reveal that if the prior information has good enough quality, L1-L1 minimization improves the performance of CS dramatically.

Information Theory Information Theory

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