A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics
Background and objectives Over the past two decades, medical imaging has been
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
A comprehensive survey analysis for present solutions of medical image fusion and future directions
OS Faragallah, H El-Hoseny, W El-Shafai… - IEEE …, 2020 - ieeexplore.ieee.org
The track of medical imaging has witnessed several advancements in the last years. Several
medical imaging modalities have appeared in the last decades including X-ray, Computed …
medical imaging modalities have appeared in the last decades including X-ray, Computed …
[Retracted] Brain Tumor Detection and Classification by MRI Using Biologically Inspired Orthogonal Wavelet Transform and Deep Learning Techniques
M Arif, F Ajesh, S Shamsudheen… - Journal of …, 2022 - Wiley Online Library
Radiology is a broad subject that needs more knowledge and understanding of medical
science to identify tumors accurately. The need for a tumor detection program, thus …
science to identify tumors accurately. The need for a tumor detection program, thus …
Parameter adaptive unit-linking pulse coupled neural network based MRI–PET/SPECT image fusion
Medical image fusion has many applications to healthcare that is accomplished by
extracting and then combining the complementary information from multiple medical images …
extracting and then combining the complementary information from multiple medical images …
Medical image fusion via discrete stationary wavelet transform and an enhanced radial basis function neural network
Medical image fusion of images obtained via different modes can expand the inherent
information of original images, whereby the fused image has a superior ability to display …
information of original images, whereby the fused image has a superior ability to display …
[PDF][PDF] Multimodal medical image registration and fusion for quality enhancement
For the last two decades, physicians and clinical experts have used a single imaging
modality to identify the normal and abnormal structure of the human body. However, most of …
modality to identify the normal and abnormal structure of the human body. However, most of …
CSID: A novel multimodal image fusion algorithm for enhanced clinical diagnosis
SR Muzammil, S Maqsood, S Haider, R Damaševičius - Diagnostics, 2020 - mdpi.com
Technology-assisted clinical diagnosis has gained tremendous importance in modern day
healthcare systems. To this end, multimodal medical image fusion has gained great …
healthcare systems. To this end, multimodal medical image fusion has gained great …
[HTML][HTML] A new optimized configuration for capacity and operation improvement of CCHP system based on developed owl search algorithm
Y Cao, Q Wang, Z Wang, K Jermsittiparsert, M Shafiee - Energy Reports, 2020 - Elsevier
One of the best ways to optimally consuming fossil fuel thermal energy is to utilize combined
cooling, heating, and power (CCHP) systems. In such systems, by recycling heat wasted …
cooling, heating, and power (CCHP) systems. In such systems, by recycling heat wasted …
Bearing fault diagnosis method based on multi-source heterogeneous information fusion
K Zhang, T Gao, H Shi - Measurement Science and Technology, 2022 - iopscience.iop.org
Bearing fault diagnosis is a critical component of the mechanical equipment monitoring
system. In the complex and harsh environment in which bearings operate, the fault …
system. In the complex and harsh environment in which bearings operate, the fault …
[PDF][PDF] Identification of thoracic diseases by exploiting deep neural networks
With the increasing demand for doctors in chest related diseases, there is a 15%
performance gap every five years. If this gap is not filled with effective chest disease …
performance gap every five years. If this gap is not filled with effective chest disease …