Hyper-Fusion Network for Semi-Automatic Segmentation of Skin Lesions

Autor: Bi, Lei, Fulham, Michael, Kim, Jinman

Automatic skin lesion segmentation methods based on fully convolutional networks (FCNs) are regarded as the state-of-the-art for accuracy. When there are, however, insufficient training data to cover all the variations in skin lesions, where lesions

Externí odkaz: http://arxiv.org/abs/2412.10816

SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model

Autor: Chan, Trevor J., Sahni, Aarush, Fang, Yijin, Li, Jie, Luthra, Alisha, Pouch, Alison, Rajapakse, Chamith S.

We introduce SAM3D, a new approach to semi-automatic zero-shot segmentation of 3D images building on the existing Segment Anything Model. We achieve fast and accurate segmentations in 3D images with a four-step strategy involving: user prompting with

Externí odkaz: http://arxiv.org/abs/2405.06786

Artificial intelligence versus semi-automatic segmentation of the inferior alveolar canal on cone-beam computed tomography scans: A pilot study.

Autor: Issa J; Chair of Practical Clinical Dentistry, Department of Diagnostics, Poznan University of Medical Sciences, Poland.; Doctoral School, Poznan University of Medical Sciences, Poland., Kulczyk T; Chair of Practical Clinical Dentistry, Department of Diagnostics, Poznan University of Medical Sciences, Poland., Rychlik M; Division of Virtual Engineering, Institute of Applied Mechanics, Poznan University of Technology, Poland., Czajka-Jakubowska A; Department of Orthodontics and Temporomandibular Disorders, Poznan University of Medical Sciences, Poland., Olszewski R; Department of Oral and Maxillofacial Surgery, Cliniques Universitaires Saint Luc, Brussels, Belgium.; Oral and Maxillofacial Surgery Research Lab (OMFS), Neuro Musculo Skeletal Lab (NMSK), Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium., Dyszkiewicz-Konwińska M; Chair of Practical Clinical Dentistry, Department of Diagnostics, Poznan University of Medical Sciences, Poland.

Publikováno v: Dental and medical problems [Dent Med Probl] 2024 Nov-Dec; Vol. 61 (6), pp. 893-899.

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Learning label diffusion maps for semi-automatic segmentation of lung CT images with COVID-19

Autor: Bruzadin, Aldimir, Boaventura, Maurílio, Colnago, Marilaine, Negri, Rogério Galante, Casaca, Wallace

Publikováno v: In Neurocomputing 14 February 2023 522:24-38