1 code implementation • 6 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.
1 code implementation • 8 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.
1 code implementation • 30 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.
2 code implementations • 1 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.
1 code implementation • 21 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.
1 code implementation • 7 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.
1 code implementation • 17 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.