Artifact removal for unpaired thorax CBCT images using a feature fusion residual network and contextual loss.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of applied clinical medical physics"
DOI: 10.1002/acm2.13968
Abstract: BACKGROUND AND OBJECTIVE Cone-beam computed tomography (CBCT) has become a more and more active cutting-edge topic in the international computed tomography (CT) research due to its advantages of fast scanning speed, high ray utilization rate… read more here.
Keywords: cbct images; feature fusion; loss; thorax cbct ... See more keywords
LGF‐Net: A multi‐scale feature fusion network for thyroid nodule ultrasound image classification
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.70149
Abstract: Abstract Background Thyroid cancer is one of the most common cancers in clinical practice, and accurate classification of thyroid nodule ultrasound images is crucial for computer‐aided diagnosis. Models based on a convolutional neural network (CNN)… read more here.
Keywords: classification; nodule; feature fusion; multi scale ... See more keywords
Computer‐aided diagnosis of retinal diseases using multidomain feature fusion
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22379
Abstract: In this article, an attempt is made to combine both transform and spatial domain features to increase the accuracy, sensitivity, and specificity for the classification of retinal diseases. Papilloedema, macular edema, glaucoma, diabetic retinopathy (DR),… read more here.
Keywords: feature; feature fusion; fusion; computer aided ... See more keywords
FFCAEs: An efficient feature fusion framework using cascaded autoencoders for the identification of gliomas
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22820
Abstract: Intracranial tumors arise from constituents of the brain and its meninges. Glioblastoma (GBM) is the most common adult primary intracranial neoplasm and is categorized as high‐grade astrocytoma according to the World Health Organization (WHO). The… read more here.
Keywords: ffcaes efficient; fusion; feature fusion; cascaded autoencoders ... See more keywords
Lightweight Skin Lesion Segmentation Network With Multi‐Scale Feature Fusion Interaction
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.70176
Abstract: The existing segmentation algorithms have many problems, such as a large number of parameters, a complicated calculation process, and difficulty in accurately segmenting skin lesion areas with hair interference, blurred edges, and unclear lesion features.… read more here.
Keywords: segmentation; feature; skin lesion; feature fusion ... See more keywords
Diffuse Large B-cell Lymphoma Segmentation in PET-CT Images via Hybrid Learning for Feature Fusion.
Sign Up to like & getrecommendations! Published in 2021 at "Medical physics"
DOI: 10.1002/mp.14847
Abstract: PURPOSE Diffuse large B-cell lymphoma (DLBCL) is an aggressive type of lymphoma with high mortality and poor prognosis that especially has a high incidence in Asia. Accurate segmentation of DLBCL lesions is crucial for clinical… read more here.
Keywords: dlbcl; feature; segmentation; feature fusion ... See more keywords
Attention-enhanced multiscale feature fusion network for pancreas and tumor segmentation.
Sign Up to like & getrecommendations! Published in 2024 at "Medical physics"
DOI: 10.1002/mp.17385
Abstract: BACKGROUND Accurate pancreas and pancreatic tumor segmentation from abdominal scans is crucial for diagnosing and treating pancreatic diseases. Automated and reliable segmentation algorithms are highly desirable in both clinical practice and research. PURPOSE Segmenting the pancreas… read more here.
Keywords: tumor segmentation; segmentation; attention; feature fusion ... See more keywords
A Novel Multiscale Feature Fusion Neural Network for Analyzing Uncertain Dynamic Characteristics of Laminated Structures
Sign Up to like & getrecommendations! Published in 2025 at "Polymer Composites"
DOI: 10.1002/pc.30052
Abstract: Conventional Monte Carlo simulations (MCS) face numerous challenges in addressing the unpredictable dynamic features of composite structures, such as excessive data volume, low computational efficiency, and limited applicability. By fully considering the stochasticity of geometric… read more here.
Keywords: dynamic characteristics; characteristics laminated; feature fusion; network ... See more keywords
Smoky vehicle detection based on multi-feature fusion and ensemble neural networks
Sign Up to like & getrecommendations! Published in 2018 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-6248-2
Abstract: Existing methods of smoky vehicle detection from the traffic flow are inefficiency and need a large number of workers. To solve this issue, we propose an automatic smoky vehicle detection method based on multi-feature fusion… read more here.
Keywords: detection; smoky vehicle; vehicle detection; vehicle ... See more keywords
Feature fusion analysis of big cognitive data
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-7536-1
Abstract: Cognitive computing is one kind of affective social computing, and becomes a research hotspot now. The traditional feature fusion method has the disadvantages to process big cognitive data, such as high redundancy, less efficient operation,… read more here.
Keywords: cognitive data; big cognitive; analysis; feature fusion ... See more keywords
SaRPFF: A self-attention with register-based pyramid feature fusion module for enhanced rice leaf disease (RLD) detection
Sign Up to like & getrecommendations! Published in 2024 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-025-20696-3
Abstract: Detecting objects across varying scales is still a challenge in computer vision, particularly in agricultural applications like Rice Leaf Disease (RLD) detection, where objects exhibit significant scale variations (SV). Conventional object detection (OD) like Faster… read more here.
Keywords: detection; register; attention; pyramid feature ... See more keywords