Radiological images and machine learning: trends, perspectives, and prospects
The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …
research area that is expected to grow in the next five to ten years. Recent advances in …
Review on 2D and 3D MRI image segmentation techniques
Background: Magnetic Resonance Imaging is most widely used for early diagnosis of
abnormalities in human organs. Due to the technical advancement in digital image …
abnormalities in human organs. Due to the technical advancement in digital image …
Voltage and frequency control with adaptive reaction time in multiple-clock-domain processors
Q Wu, P Juang, M Martonosi… - … Symposium on High …, 2005 - ieeexplore.ieee.org
Dynamic voltage and frequency scaling (DVFS) is a widely used method for energy-efficient
computing. In this paper, we present a new intra-task online DVFS scheme for multiple clock …
computing. In this paper, we present a new intra-task online DVFS scheme for multiple clock …
Segmentation of brain MRI using wavelet transform and grammatical bee colony
Multimodal Magnetic Resonance Imaging (MRI) is an imaging technique widely used in the
diagnosis and treatment planning of patients. Lesion segmentation of brain MRI is one of the …
diagnosis and treatment planning of patients. Lesion segmentation of brain MRI is one of the …
Brain tumor segmentation in MRI images using a hybrid deep network based on patch and pixel
F Derikvand, H Khotanlou - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
In recent years, many segmentation methods have been proposed for brain tumor
segmentation, among them deeplearning approaches have good performance and have …
segmentation, among them deeplearning approaches have good performance and have …
A novel ALM based security framework for block chain in healthcare platform
DP Anjelin, SG Kumar - … Journal of System Assurance Engineering and …, 2024 - Springer
Blockchain technology may be a recent advancement and offers a ground-breaking
technique for kee** the knowledge for an extended time and completing transactions like …
technique for kee** the knowledge for an extended time and completing transactions like …
Learning aided structures for image segmentation in complex background
M Barthakur, KK Sarma… - … European conference on …, 2017 - ieeexplore.ieee.org
Image segmentation is the fundamental step many algorithm. In this paper, a simplified
neuro-computing structure in feed forward form for use in segmentation of images in …
neuro-computing structure in feed forward form for use in segmentation of images in …
Neural network methods for image segmentation
M Barthakur, KK Sarma, N Mastorakis - International Conference on …, 2017 - Springer
Segmentation is the fundamental step in many image processing algorithms. In this paper, a
simplified neuro-computing structure in feed forward form for use in segmentation of images …
simplified neuro-computing structure in feed forward form for use in segmentation of images …
Neural network methods for image segmentation
N Mastorakis - Applied Physics, System Science and Computers …, 2018 - books.google.com
Segmentation is the fundamental step in many image processing algorithms. In this paper, a
simplified neuro-computing structure in feed forward form for use in segmentation of images …
simplified neuro-computing structure in feed forward form for use in segmentation of images …
Investigations of videofluoroscopy via machine learning: Novel ways for swallowing disorders assessment
Z Zhang - 2021 - d-scholarship.pitt.edu
Videofluoroscopic swallow studies are widely used in clinical and research settings to
assess swallow function and to determine physiological impairments, diet …
assess swallow function and to determine physiological impairments, diet …