Results 291 to 300 of about 1,689,718 (367)

Enhancing Diagnostic Accuracy: A Hybrid Approach to Mitigate Speckle and Rician Noise in Medical Images

Naveenkumar Jayakumar
openalex   +2 more sources

Optimal performance of simple low-cost optical physical unclonable functions resilient to machine learning attacks : ¹Eulambia advanced technologies Ltd., Athens, Greece, ²Department of informatics & Telecommunications, National and kapodistrian university of Athens, Athens, Greece. [PDF]

Sci Rep
Akriotou M, Bartsokas T, Veinidis C, Syvridis D.   +3 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Semi-Supervised Capsule cGAN for Speckle Noise Reduction in Retinal OCT Images

IEEE Transactions on Medical Imaging, 2021
Speckle noise is the main cause of poor optical coherence tomography (OCT) image quality. Convolutional neural networks (CNNs) have shown remarkable performances for speckle noise reduction.
Meng Wang, Weifang Zhu, Kai Yu, Zhongyue Chen, Fei Shi, Yi Zhou, Yuhui Ma, Yuanyuan Peng, D. Bao, Shuanglang Feng, Lei Ye, Dehui Xiang, Xinjian Chen   +12 more
semanticscholar   +1 more source

Speckle Noise Reduction for OCT Images Based on Image Style Transfer and Conditional GAN

IEEE journal of biomedical and health informatics, 2021
Raw optical coherence tomography (OCT) images typically are of low quality because speckle noise blurs retinal structures, severely compromising visual quality and degrading performances of subsequent image analysis tasks. In our previous study (Ma et al.
Yi Zhou, Kai Yu, Meng Wang, Yuhui Ma, Yuanyuan Peng, Zhongyue Chen, Weifang Zhu, Fei Shi, Xinjian Chen   +8 more
semanticscholar   +1 more source

KAZE-SAR: SAR Image Registration Using KAZE Detector and Modified SURF Descriptor for Tackling Speckle Noise

IEEE Transactions on Geoscience and Remote Sensing, 2021
Synthetic aperture radar (SAR) image registration is still a challenging task in remote sensing. The scale-invariant feature transform (SIFT) method and its extensions are most widely used feature detectors in SAR images.
Mohammadreza Pourfard, Tahmineh Hosseinian, R. Saeidi, S. A. Motamedi, M. Abdollahifard, Reza Mansoori, R. Safabakhsh   +6 more
semanticscholar   +1 more source

A deep neural network learning‐based speckle noise removal technique for enhancing the quality of synthetic‐aperture radar images

Concurrency and Computation, 2021
The speckle noise present in synthetic‐aperture radar (SAR) images is responsible for hindering the extraction of the exact information that needs to be utilized for potential remote sensing applications.
Mohan Ellappan, A. Rajesh, G. Sunitha, Reddy Madhavi Konduru, J. Avanija, L. G. Babu   +5 more
semanticscholar   +1 more source

A Review on Despeckling Filters in Ultrasound Images for Speckle Noise Reduction

2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2021
Ultrasound imaging is the most generally used in medical diagnosis and it is corrupted by speckle noise, which is multiplicative. For a better diagnosis, there is also a need to decrease the speckle noise in ultrasound images.
Shivam Kumar Pal, Ankur Bhardwaj, A. P. Shukla   +2 more
semanticscholar   +1 more source

MLMVN in Speckle Noise Filtering

2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP), 2020
In this paper, we use the multilayer neural network with multi-valued neurons (MLMVN) as an intelligent tool for speckle noise filtering. MLMVN is a complex-valued feedforward neural network, which was successfully used for solving various problems including classification, prediction and additive noise filtering.
Igor Aizenberg, Olivia Keohane, Alejandro Lara   +2 more
openaire   +1 more source

A Speckle Noise Removal Method

Circuits, Systems, and Signal Processing, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Saadia, Ayesha, Rashdi, Adnan
openaire   +1 more source