Simulation Research in Gastrointestinal and Urologic Care-Challenges and Opportunities: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases and National Institute of Biomedical Imaging and Bioengineering Workshop.

Autor: Aggarwal R; Department of Surgery and Steinberg Center for Simulation and Interactive Learning, Faculty of Medicine, McGill University, Montreal, Quebec, Canada., Brown KM; Department of Surgery and Perioperative Care, Dell Medical School, University of Texas, Austin, TX., de Groen PC; Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Minnesota, Minneapolis, MN., Gallagher AG; ASSERT Center, College of Medicine and Health, University College Cork, Ireland, and Faculty of Life and Health Sciences, Ulster University, Belfast, UK., Henriksen K; Agency for Healthcare Research and Quality, Rockville, MD., Kavoussi LR; Department of Urology, Northwell Hofstra School of Medicine, Nassau, NY., Peng GCY; National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD., Ritter EM; Department of Surgery, Uniformed Services University for the Health Sciences, Bethesda, MD., Silverman E; Department of Surgery, Tufts University School of Medicine, Boston, MA., Wang KK; Division of Gastroenterology and Hepatology, Department of Medicine, Mayo School of Medicine, Rochester, MN., Andersen DK; Division of Digestive Diseases and Nutrition, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD.

Publikováno v: Annals of surgery [Ann Surg] 2018 Jan; Vol. 267 (1), pp. 26-34.

Palette‐based colour normalization for histopathology images

Autor: Shengzhe Shi, Yanyan Wang, Kaikai Zhang, Qingqing Wang, Sheng Liu, Chun Wang

Publikováno v: IET Image Processing, Vol 18, Iss 13, Pp 4368-4380 (2024)

Abstract With the emergence of computer‐aided diagnostic (CAD) systems, the speed of histopathological image analysis and the accuracy of cancer detection have considerably improved. However, the appearance of histopathological slides can vary depe

Externí odkaz: https://doaj.org/article/7fdc585d49f342d19dc870218a15fc18

LPAM: A lightweight medical segmentation network based on Mamba improved by prompt attention

Autor: Kaiqi Hu, Chudong Xu

Publikováno v: IET Image Processing, Vol 18, Iss 12, Pp 3545-3555 (2024)

Abstract Presently, State Space Models (SSMs), including frameworks like Mamba, have been incorporated into the realm of computer vision. These models not only sustain remote interactions and encapsulate global semantic information effectively, but a

Externí odkaz: https://doaj.org/article/6aa26a352af04dcea4091c8a7a50c728

Electrical impedance tomography image reconstruction for lung monitoring based on ensemble learning algorithms1

Autor: Areen K. Al‐Bashir, Duha H. Al‐Bataiha, Mariem Hafsa, Mohammad A. Al‐Abed, Olfa Kanoun

Publikováno v: Healthcare Technology Letters, Vol 11, Iss 5, Pp 271-282 (2024)

Abstract Electrical impedance tomography (EIT) is a promising non‐invasive imaging technique that visualizes the electrical conductivity of an anatomic structure to form based on measured boundary voltages. However, the EIT inverse problem for the

Externí odkaz: https://doaj.org/article/bb10a32807b4448f9a2c41169e77e786

Feature ensemble network for medical image segmentation with multi‐scale atrous transformer

Autor: Di Gai, Yuhan Geng, Xia Huang, Zheng Huang, Xin Xiong, Ruihua Zhou, Qi Wang

Publikováno v: IET Image Processing, Vol 18, Iss 11, Pp 3082-3092 (2024)

Abstract Recent years have witnessed notable advancements in medical image segmentation through deep convolutional neural networks. However, a notable limitation lies in the local operation of convolution, which hinders the ability to fully exploit g

Externí odkaz: https://doaj.org/article/7c2cf03fb02e4d1e9f3c9e2781964584