Results 241 to 250 of about 9,856,837 (311)

Improved YOLOv8-seg for laryngeal structure recognition in medical images. [PDF]

Am J Transl Res
Cui H, Wu J, Li T, Zou Z, Guo W, Liu L, Zhang Q, Huang X.   +7 more
europepmc   +1 more source

Improving Colorectal Cancer Screening and Risk Assessment through Predictive Modeling on Medical Images and Records. [PDF]

Am J Pathol
Jiang S, Robinson C, Anderson J, Hisey W, Butterly L, Suriawinata A, Hassanpour S.   +6 more
europepmc   +1 more source

Improvement of medical images with multi-objective genetic algorithm and adaptive morphological transformations. [PDF]

Sci Rep
Moradzadeh S, Mehrdad V.
europepmc   +1 more source

Medical slice transformer for improved diagnosis and explainability on 3D medical images with DINOv2. [PDF]

Sci Rep
Müller-Franzes G, Khader F, Siepmann R, Han T, Kather JN, Nebelung S, Truhn D.   +6 more
europepmc   +1 more source

A systematic review of the hybrid machine learning models for brain tumour segmentation and detection in medical images. [PDF]

Front Artif Intell
Netshamutshedzi N, Netshikweta R, Ndogmo JC, Obagbuwa IC.   +3 more
europepmc   +1 more source

Modelo mecanobiológico de una tibia humana para determinar su respuesta ante estímulos mecánicos externos

Revista Cubana de Investigaciones Biomédicas
Yosbel Angel Cisneros Hidalgo, Raide Alfonso González Carbonell, Armando Ortiz Prado, Victor Hugo Jacobo Almendáriz, Antonio Puente Álvarez   +4 more
doaj  

RETRACTION: Recombinant Nanobody Against Muc1 Tandem Repeats Inhibits Growth, Invasion, Metastasis, and Vascularization of Spontaneous Mouse Mammary Tumors

Molecular Oncology, EarlyView.
RETRACTION: P. Merikhian, B. Darvishi, N. Jalili, M. R. Esmailinejad, A. S. Khatibi, S. M. Kalbolandi, M. Salehi, M. Mosayebzadeh, M. S. Barough, K. Majidzadeh‐A, F. Yadegari, F. Rahbarizadeh, and L. Farahmand, “Recombinant Nanobody Against Muc1 Tandem Repeats Inhibits Growth, Invasion, Metastasis, and Vascularization of Spontaneous Mouse Mammary ...
wiley   +1 more source

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Segmentation of medical images

Image and Vision Computing, 1993
Abstract Segmentation and labelling remains the weakest step in many medical vision applications. This paper illustrates an approach based on generic modules which are designed to solve typical problems encountered in various applications, and which are controllable through adaptation of their parameters.
Rudi Deklerck, Jan Cornelis 0001, Michel Bister   +2 more
openaire   +3 more sources