Results 91 to 100 of about 56,033 (246)

Dynamic Mode Decomposition (DMD) for Low‐Latency Real‐Time Cardiac MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To demonstrate dynamic mode decomposition (DMD) for high spatiotemporal low‐latency online reconstruction in 2D real‐time cardiac MRI. Methods DMD was applied to 2D spiral balanced steady state free precession (bSSFP) real‐time adult and fetal cardiac MRI at 0.55 T, with data from 10 healthy adult volunteers (3F/7M; age: 21–49; BMI: 20–
Ecrin Yagiz, Bilal Tasdelen, Ibrahim K. Ozaslan, Mihailo R. Jovanovic, Ye Tian, Krishna S. Nayak   +5 more
wiley   +1 more source

Text Data Security Using LCG and CBC with Steganography Technique on Digital Image

Journal of Applied Informatics and Computing
This research proposes a text data security method using a combination of Linear Congruential Generator (LCG), Advanced Encryption Standard (AES) Cipher Block Chaining (CBC) mode, and Least Significant Bit (LSB) steganography technique on digital images.
Muhammad Wildan, Wahid Miftahul Ashari
doaj   +1 more source

Computational intelligence-based steganalysis comparison for RCM-DWT and PVA-MOD methods

Automatika, 2019
This research article proposes data hiding technique for improving the data hiding procedure and securing the data transmission with the help of contrast mapping technique along with advanced data encryption standard.
T. D. Sairam, K. Boopathybagan
doaj   +1 more source

DeepRelaxo: Fast Mono‐Exponential Magnitude Brain R2* Mapping With Reduced Echoes Using Self‐Supervised Deep Learning

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose We introduce DeepRelaxo, a fast and generalizable deep learning method for estimating brain R2* maps from multi‐echo gradient echo (ME‐GRE) acquisitions with arbitrary echo configurations, including shortened echo trains for accelerated scans.
Samiha Prima, Zhuang Xiong, Alan H. Wilman, Hongfu Sun   +3 more
wiley   +1 more source

Image denoising of coal dust based on fractional calculus adaptive algorithm

Gong-kuang zidonghua, 2014
In view of problem of long iteration process, unsatisfactory image denoising effect and poor texture retention capacity of traditional denoising method of coal dust image, the paper improved existing method and built an adaptive denoising algorithm based
WANG Zheng, MA Xianmi
doaj   +1 more source

Time‐Conditioned Zero‐Shot Self‐Supervised Reconstruction for Accelerated 3D Ultra‐Low‐Field MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Ultra‐low‐field (ULF) MRI provides a cost‐effective, portable imaging option but has relatively low SNR and long acquisition times compared to standard clinical scans. This study presents a time‐conditioned zero‐shot self‐supervised learning image reconstruction framework (ULF‐ZS‐SSL) to accelerate 3D‐acquired single‐coil ULF MRI ...
Mart W. J. van Straten, Beatrice Lena, Chloé Najac, Ruben van den Broek, Peter Börnert, Andrew Webb, Yiming Dong   +6 more
wiley   +1 more source

Pengiriman Citra pada Komunikasi Cahaya Tampak IEEE 802.15.7 Lapisan Fisik II.f-n

Jurnal Nasional Teknik Elektro dan Teknologi Informasi, 2016
Visible light communication (VLC) is a communication technology using visible light as a transmission medium that can have larger bandwidth than other wireless communications. VLC has a standard of IEEE 802.15.7 which has two layers. One of the layers is
Eny Sukani Rahayu, Rabani Rashif Saniy Alfarisi, Iswandi   +2 more
doaj   +1 more source

Physics‐Guided Neural Network for Quantitative Parameter Mapping Using Balanced Steady State Free Precession MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To propose a new method using a physics‐guided neural network for quantitative parameter mapping in balanced steady‐state free precession (bSSFP) imaging. Theory and Methods We trained physics‐guided neural networks with a multilayer perceptron using simulated bSSFP signals generated from tissue parameters (T1$$ {T}_1 $$, T2$$ {T}_2 $$,
Hye‐Ryeong Choi, Huan Minh Luu, Sung‐Hong Park   +2 more
wiley   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source

Robust steganographic framework for securing sensitive healthcare data of telemedicine using convolutional neural network

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Data is the key element that runs the modern society. Large amounts of data are being released day by day as a result of many activities. The digital data is transferred through the Internet which may be vulnerable to attacks while transmitting. Especially, the medical data is observed to be of at most importance.
Rupa Ch, Venkayya Yadlapalli, Suhana Sulthana Sk, G. Thippa Reddy, Sandeep Kautish   +4 more
wiley   +1 more source