Medical image fusion based on transfer learning techniques and coupled neural P systems
Medical image fusion is an essential task for clinical diagnosis because it allows physicians
to make more accurate diagnoses. Up to now, many medical image synthesis algorithms …
to make more accurate diagnoses. Up to now, many medical image synthesis algorithms …
[HTML][HTML] Medical image fusion quality assessment based on conditional generative adversarial network
L Tang, Y Hui, H Yang, Y Zhao, C Tian - Frontiers in Neuroscience, 2022 - frontiersin.org
Multimodal medical image fusion (MMIF) has been proven to effectively improve the
efficiency of disease diagnosis and treatment. However, few works have explored dedicated …
efficiency of disease diagnosis and treatment. However, few works have explored dedicated …
CAFseg: A Semantic segmentation network with cross aggregation fusion strategy for RGB-thermal semantic segmentation
S Yi, L Wu, X Liu, J Li, G Jiang - Infrared Physics & Technology, 2024 - Elsevier
Semantic segmentation utilises the RGB-Thermal (RGB-T) source images with the capacity
of provide pixel-level prediction for surrounding scenes in harsh imaging conditions …
of provide pixel-level prediction for surrounding scenes in harsh imaging conditions …
Deep Multimodal Fusion of Data with Heterogeneous Dimensionality via Projective Networks
The use of multimodal imaging has led to significant improvements in the diagnosis and
treatment of many diseases. Similar to clinical practice, some works have demonstrated the …
treatment of many diseases. Similar to clinical practice, some works have demonstrated the …
DRCM: a disentangled representation network based on coordinate and multimodal attention for medical image fusion
W Huang, H Zhang, Y Cheng, X Quan - Frontiers in Physiology, 2023 - frontiersin.org
Recent studies on medical image fusion based on deep learning have made remarkable
progress, but the common and exclusive features of different modalities, especially their …
progress, but the common and exclusive features of different modalities, especially their …
[HTML][HTML] Shedding light on ai in radiology: A systematic review and taxonomy of eye gaze-driven interpretability in deep learning
X-ray imaging plays a crucial role in diagnostic medicine. Yet, a significant portion of the
global population lacks access to this essential technology due to a shortage of trained …
global population lacks access to this essential technology due to a shortage of trained …
DuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac …
Single-Photon Emission Computed Tomography (SPECT) is widely applied for the
diagnosis of coronary artery diseases. Low-dose (LD) SPECT aims to minimize radiation …
diagnosis of coronary artery diseases. Low-dose (LD) SPECT aims to minimize radiation …
[HTML][HTML] Multimodal Machine Learning Guides Low Carbon Aeration Strategies in Urban Wastewater Treatment
The potential for reducing greenhouse gas (GHG) emissions and energy consumption in
wastewater treatment can be realized through intelligent control, with machine learning (ML) …
wastewater treatment can be realized through intelligent control, with machine learning (ML) …
[PDF][PDF] 基于多尺度影像融合的气缸盖内壁热疲劳损伤检测方法
李泉良， 王肖霞， 杨风暴 - Laser & Optoelectronics Progress, 2023 - researching.cn
摘要针对气缸盖内壁热场数据重复率高, 冗余大导致的小采样率下影像难以重构的问题,
利用多个单尺度重构影像的融合, 提出一种适用于小样本的气缸盖内壁热疲劳损伤检测方法 …
利用多个单尺度重构影像的融合, 提出一种适用于小样本的气缸盖内壁热疲劳损伤检测方法 …
INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis
Synthesizing information from multiple data sources plays a crucial role in the practice of
modern medicine. Current applications of artificial intelligence in medicine often focus on …
modern medicine. Current applications of artificial intelligence in medicine often focus on …