Automated Detection of Infection in Diabetic Foot Ulcer Using Pre-trained Fast Convolutional Neural Network with U++net

A frequent consequence of diabetes and a significant contributor to morbidity and mortality is diabetic foot ulcer (DFU).Early detection and appropriate management of DFUs are essential to prevent complications such as infections and lower extremity amputations. In recent years, medical imaging and...

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Veröffentlicht in:	SN computer science Jg. 5; H. 6; S. 705
Hauptverfasser:	Murthy, S. V. N., Bhargavi, Kovvuri N., Isaac, Samson, N.Ganesh, E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Singapore Springer Nature Singapore 01.08.2024 Springer Nature B.V
Schlagworte:	Accuracy Advanced Computing and Data Sciences Algorithms Amputation Artificial intelligence Artificial neural networks Automation Classification Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data analysis Data Structures and Information Theory Datasets Diabetes Foot diseases Heat detection Illumination Image acquisition Image enhancement Image quality Impact analysis Infections Information Systems and Communication Service Ischemia Leg ulcers Literature reviews Machine learning Medical imaging Medical research Neural networks Original Research Patients Pattern Recognition and Graphics Performance evaluation Professionals Quality of life Shades Software Engineering/Programming and Operating Systems Temperature Ulcers Vision Pre-trained fast convolutional neural network Diabetic foot ulcer Diabetic foot infection network with the adam optimizer
ISSN:	2661-8907, 2662-995X, 2661-8907
Online-Zugang:	Volltext
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