Search Results for author: Miguel Xochicale

Found 7 papers, 7 papers with code

Towards a Simple Framework of Skill Transfer Learning for Robotic Ultrasound-guidance Procedures

1 code implementation6 May 2023 Tsz Yan Leung, Miguel Xochicale

We then identify the need of appropriate sampling techniques, computationally efficient neural networks models that lead to the proposal of a simple framework of skill transfer learning for real-time applications in robotic ultrasound-guidance procedures.

Time Series Transfer Learning

Towards Realistic Ultrasound Fetal Brain Imaging Synthesis

1 code implementation8 Apr 2023 Michelle Iskandar, Harvey Mannering, Zhanxiang Sun, Jacqueline Matthew, Hamideh Kerdegari, Laura Peralta, Miguel Xochicale

The results of this work illustrate the potential of GAN-based methods to synthesise realistic high-resolution ultrasound images, leading to future work with other fetal brain planes, anatomies, devices and the need of a pool of experts to evaluate synthesised images.

Super-Resolution

A Machine Learning Case Study for AI-empowered echocardiography of Intensive Care Unit Patients in low- and middle-income countries

1 code implementation30 Dec 2022 Miguel Xochicale, Louise Thwaites, Sophie Yacoub, Luigi Pisani, Phung-Nhat Tran-Huy, Hamideh Kerdegari, Andrew King, Alberto Gomez

We present a Machine Learning (ML) study case to illustrate the challenges of clinical translation for a real-time AI-empowered echocardiography system with data of ICU patients in LMICs.

Model Selection

Empirical Study of Quality Image Assessment for Synthesis of Fetal Head Ultrasound Imaging with DCGANs

2 code implementations1 Jun 2022 Thea Bautista, Jacqueline Matthew, Hamideh Kerdegari, Laura Peralta Pereira, Miguel Xochicale

In this work, we present an empirical study of DCGANs, including hyperparameter heuristics and image quality assessment, as a way to address the scarcity of datasets to investigate fetal head ultrasound.

Image Quality Assessment

AI-enabled Assessment of Cardiac Systolic and Diastolic Function from Echocardiography

1 code implementation21 Mar 2022 Esther Puyol-Antón, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark K. Elliott, Vishal Mehta, Haotian Gu, Miguel Xochicale, Alberto Gomez, Christopher A. Rinaldi, Martin Cowie, Phil Chowienczyk, Reza Razavi, Andrew P. King

In this work we propose for the first time an AI approach for deriving advanced biomarkers of systolic and diastolic LV function from 2-D echocardiography based on segmentations of the full cardiac cycle.

Management

Piloting Diversity and Inclusion Workshops in Artificial Intelligence and Robotics for Children

1 code implementation7 Mar 2022 Antonio Badillo-Perez, Donato Badillo-Perez, Diego Coyotzi-Molina, Dago Cruz, Rocio Montenegro, Leticia Vazquez, Miguel Xochicale

In this paper, we present preliminary work from a pilot workshop that aimed to promote diversity and inclusion for fundamentals of Artificial Intelligence and Robotics for Children (air4children) in the context of developing countries.

Nonlinear methods to quantify Movement Variability in Human-Humanoid Interaction Activities

1 code implementation17 Oct 2018 Miguel Xochicale, Chirs Baber

Human movement variability arises from the process of mastering redundant (bio)mechanical degrees of freedom to successfully accomplish any given motor task where flexibility and stability of many possible joint combinations helps to adapt to environment conditions.

Time Series Time Series Analysis

Cannot find the paper you are looking for? You can Submit a new open access paper.