Feature enhancement framework for brain tumor segmentation and classification
Automatic medical image analysis is one of the key tasks being used by the medical
community for disease diagnosis and treatment planning. Statistical methods are the major …
community for disease diagnosis and treatment planning. Statistical methods are the major …
Denoising of magnetic resonance imaging using Bayes shrinkage based fused wavelet transform and autoencoder based deep learning approach
M Juneja, SK Saini, S Kaul, R Acharjee… - … Signal Processing and …, 2021 - Elsevier
Denoising of medical images is of great concern as it plays a significant role in performance
of computer aided diagnosis (CAD) systems. In real life scenarios, various conditions like …
of computer aided diagnosis (CAD) systems. In real life scenarios, various conditions like …
Adaptive noise variance estimation in BayesShrink
M Hashemi, S Beheshti - IEEE Signal Processing Letters, 2009 - ieeexplore.ieee.org
A method of noise variance estimation in BayesShrink image denoising is presented. The
proposed approach competes with the well known MAD-based method and outperforms this …
proposed approach competes with the well known MAD-based method and outperforms this …
Performance analysis of reshaped Gabor filter for removing the Rician distributed noise in brain MR images
V Kumar, S Srivastava - … , Part H: Journal of Engineering in …, 2022 - journals.sagepub.com
Magnetic Resonance Imaging (MRI) is an essential clinical tool for detecting the
abnormalities such as tumors and clots in the human brain. The brain MR images are …
abnormalities such as tumors and clots in the human brain. The brain MR images are …
Contrastive blind denoising autoencoder for real time denoising of industrial IoT sensor data
S Langarica, F Núñez - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
In an industrial IoT setting, ensuring the quality of sensor data is a must when data-driven
algorithms operate on the upper layers of the control system. Unfortunately, the common …
algorithms operate on the upper layers of the control system. Unfortunately, the common …
Blood vessel segmentation in en-face OCTA images: a frequency based method
A Breger, F Goldbach, BS Gerendas… - Medical Imaging …, 2022 - spiedigitallibrary.org
Optical coherence tomography angiography (OCTA) is a novel noninvasive imaging
modality for visualization of retinal blood flow in the human retina. Using specific OCTA …
modality for visualization of retinal blood flow in the human retina. Using specific OCTA …
[PDF][PDF] A novel hybrid method for segmentation and analysis of brain MRI for tumor diagnosis
It is difficult to accurately segment brain MRI in the complex structures of brain tumors,
blurred borders, and external variables such as noise. Much research in developing as well …
blurred borders, and external variables such as noise. Much research in developing as well …
[PDF][PDF] A literature survey on ambient noise analysis for underwater acoustic signals
S Sadaf, P Yashaswini, S Halagur, F Khan… - Int J Comput Eng …, 2015 - academia.edu
Transmitting data with water as the medium is called underwater communication.
Electromagnetic signals are better attenuated in water than sound. Hence it is the most …
Electromagnetic signals are better attenuated in water than sound. Hence it is the most …
Deep Learning Methods for Intelligent Cyber-Physical Systems
SAL Chavira - 2023 - search.proquest.com
Cyber-physical systems (CPSs) have emerged in recent years as a new paradigm that
merges several technologies to allow the interface between the physical and the cybernetic …
merges several technologies to allow the interface between the physical and the cybernetic …