From Nano to Macro: Overview of the IEEE Bio Image and Signal Processing Technical Committee

no code implementations • 31 Oct 2022 • Selin Aviyente, Alejandro Frangi, Erik Meijering, Arrate Muñoz-Barrutia, Michael Liebling, Dimitri Van De Ville, Jean-Christophe Olivo-Marin, Jelena Kovačević, Michael Unser

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing.

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

no code implementations • 17 Nov 2021 • Javier Ortega-Garcia, Julian Fierrez, Fernando Alonso-Fernandez, Javier Galbally, Manuel R Freire, Joaquin Gonzalez-Rodriguez, Carmen Garcia-Mateo, Jose-Luis Alba-Castro, Elisardo Gonzalez-Agulla, Enrique Otero-Muras, Sonia Garcia-Salicetti, Lorene Allano, Bao Ly-Van, Bernadette Dorizzi, Josef Kittler, Thirimachos Bourlai, Norman Poh, Farzin Deravi, Ming NR Ng, Michael Fairhurst, Jean Hennebert, Andreas Humm, Massimo Tistarelli, Linda Brodo, Jonas Richiardi, Andrezj Drygajlo, Harald Ganster, Federico M Sukno, Sri-Kaushik Pavani, Alejandro Frangi, Lale Akarun, Arman Savran

It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware.

Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound

no code implementations • 11 Aug 2021 • Shuangchi He, Zehui Lin, Xin Yang, Chaoyu Chen, Jian Wang, Xue Shuang, Ziwei Deng, Qin Liu, Yan Cao, Xiduo Lu, Ruobing Huang, Nishant Ravikumar, Alejandro Frangi, Yuanji Zhang, Yi Xiong, Dong Ni

In this study, we build a novel multi-label learning (MLL) scheme to identify multiple standard planes and corresponding anatomical structures of fetus simultaneously.

Contrastive Learning Image Classification +3

Contrastive Rendering for Ultrasound Image Segmentation

no code implementations • 10 Oct 2020 • Haoming Li, Xin Yang, Jiamin Liang, Wenlong Shi, Chaoyu Chen, Haoran Dou, Rui Li, Rui Gao, Guangquan Zhou, Jinghui Fang, Xiaowen Liang, Ruobing Huang, Alejandro Frangi, Zhiyi Chen, Dong Ni

However, the lack of sharp boundaries in US images still remains an inherent challenge for segmentation.

Contrastive Learning Image Segmentation +3

Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound

no code implementations • 30 Jul 2020 • Yuhao Huang, Xin Yang, Rui Li, Jikuan Qian, Xiaoqiong Huang, Wenlong Shi, Haoran Dou, Chaoyu Chen, Yuanji Zhang, Huanjia Luo, Alejandro Frangi, Yi Xiong, Dong Ni

In this study, we propose a novel Multi-Agent Reinforcement Learning (MARL) framework to localize multiple uterine SPs in 3D US simultaneously.

Multi-agent Reinforcement Learning Neural Architecture Search