Results 11 to 20 of about 6,547,057 (287)

Enhanced glaucoma detection using U-Net and U-Net+ architectures using deep learning techniques

Photodiagnosis and Photodynamic Therapy
This study compares multiple image processing and deep learning methods to demonstrate an enhanced approach to glaucoma diagnosis. The approach focuses on noise reduction using median filtering and optic disc segmentation utilizing the U-Net and U-Net ...
B.P. Pradeep kumar, Pramod K.B. Rangaiah, Robin Augustine   +2 more
doaj   +3 more sources

U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications [PDF]

IEEE Access, 2021
U-net is an image segmentation technique developed primarily for image segmentation tasks. These traits provide U-net with a high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for ...
Nahian Siddique, Sidike Paheding, Colin P. Elkin, Vijay Devabhaktuni   +3 more
doaj   +2 more sources

UIU-Net: U-Net in U-Net for Infrared Small Object Detection [PDF]

IEEE Transactions on Image Processing, 2023
Learning-based infrared small object detection methods currently rely heavily on the classification backbone network. This tends to result in tiny object loss and feature distinguishability limitations as the network depth increases. Furthermore, small objects in infrared images are frequently emerged bright and dark, posing severe demands for ...
Wu, Xin, Hong, Danfeng, Chanussot, Jocelyn   +2 more
openaire   +5 more sources

Comparative performance analysis of simple U-Net, residual attention U-Net, and VGG16-U-Net for inventory inland water bodies

Applied Computing and Geosciences, 2023
Inland water bodies play a vital role at all scales in the terrestrial water balance and Earth’s climate variability. Thus, an inventory of inland waters is crucially important for hydrologic and ecological studies and management. Therefore, the main aim
Ali Ghaznavi, Mohammadmehdi Saberioon, Jakub Brom, Sibylle Itzerott   +3 more
doaj   +4 more sources

U-Net Optimization for Hyperreflective Foci Segmentation in Retinal OCT [PDF]

Diagnostics
Background/Objectives: Hyperreflective foci (HRF) are supportive optical coherence tomography (OCT) imaging biomarkers that have been examined for their association with disease progression and severity in various retinal disorders.
Pavithra Kodiyalbail Chakrapani, Preetham Kumar, Sulatha Venkataraya Bhandary, Geetha Maiya, Shailaja Shenoy, Steven Fernandes, Prakhar Choudhary   +6 more
doaj   +2 more sources

U-Net V2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation [PDF]

2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), 2023
In this paper, we introduce U-Net v2, a new robust and efficient U-Net variant for medical image segmentation. It aims to augment the infusion of semantic information into low-level features while simultaneously refining high-level features with finer details.
Peng, Yaopeng, Sonka, Milan, Chen, Danny Z.   +2 more
openaire   +3 more sources

Enhanced glioma semantic segmentation using U-net and pre-trained backbone U-net architectures [PDF]

Scientific Reports
Gliomas are known to have different sub-regions within the tumor, including the edema, necrotic, and active tumor regions. Segmenting of these regions is very important for glioma treatment decisions and management.
Amir Khorasani
doaj   +2 more sources

U-Net-Based Medical Image Segmentation

Journal of Healthcare Engineering, 2022
Deep learning has been extensively applied to segmentation in medical imaging. U-Net proposed in 2015 shows the advantages of accurate segmentation of small targets and its scalable network architecture. With the increasing requirements for the performance of segmentation in medical imaging in recent years, U-Net has been cited academically more than ...
Xiao-Xia Yin, Le Sun, Yuhan Fu, Ruiliang Lu, Yanchun Zhang   +4 more
openaire   +3 more sources

Generalized U-Net for automatic liver segmentation and R2* estimation for assessment of iron overload using MRI [PDF]

BMC Medical Imaging
Background Although R2*-MRI is extensively validated for assessing liver iron concentration (LIC), techniques for robust and automatic liver extraction remain underdeveloped, limiting clinical workflow and adoption for automated LIC reporting. Hence this
Utsav Shrestha, Zachary R. Abramson, Stephan Kannengiesser, Xiaodong Zhong, Cara E. Morin, Aaryani Tipirneni-Sajja   +5 more
doaj   +2 more sources

Relation U-Net

2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)
ISIB ...
He, Sheng, Bao, Rina, Grant, P. Ellen, Ou, Yangming   +3 more
openaire   +3 more sources