Search Results for author: Robert Martí

Found 5 papers, 3 papers with code

MAM-E: Mammographic synthetic image generation with diffusion models

2 code implementations16 Nov 2023 Ricardo Montoya-del-Angel, Karla Sam-Millan, Joan C Vilanova, Robert Martí

Additionally, we propose using stable diffusion models for the inpainting of synthetic lesions on healthy mammograms.

Data Augmentation Image Generation

Federated Model Aggregation via Self-Supervised Priors for Highly Imbalanced Medical Image Classification

1 code implementation27 Jul 2023 Marawan Elbatel, Hualiang Wang, Robert Martí, Huazhu Fu, Xiaomeng Li

Existing federated methods under highly imbalanced datasets primarily focus on optimizing a global model without incorporating the intra-class variations that can arise in medical imaging due to different populations, findings, and scanners.

Federated Learning Image Classification +2

FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition

1 code implementation27 May 2023 Marawan Elbatel, Robert Martí, Xiaomeng Li

Representational transfer from publicly available models is a promising technique for improving medical image classification, especially in long-tailed datasets with rare diseases.

Image Classification Knowledge Distillation +4

6D Pose Estimation using an Improved Method based on Point Pair Features

no code implementations23 Feb 2018 Joel Vidal, Chyi-Yeu Lin, Robert Martí

The Point Pair Feature (Drost et al. 2010) has been one of the most successful 6D pose estimation method among model-based approaches as an efficient, integrated and compromise alternative to the traditional local and global pipelines.

6D Pose Estimation 6D Pose Estimation using RGB

Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review

no code implementations11 Dec 2017 Jose Bernal, Kaisar Kushibar, Daniel S. Asfaw, Sergi Valverde, Arnau Oliver, Robert Martí, Xavier Lladó

We present an extensive literature review of CNN techniques applied in brain magnetic resonance imaging (MRI) analysis, focusing on the architectures, pre-processing, data-preparation and post-processing strategies available in these works.

Lesion Segmentation Object Recognition +1

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