Matches in SemOpenAlex for { <https://semopenalex.org/work/W3040984225> ?p ?o ?g. }
- W3040984225 abstract "Abstract In image-based medical decision-making, different modalities of medical images of a given organ of a patient are captured. Each of these images will represent a modality that will render the examined organ differently, leading to different observations of a given phenomenon (such as stroke). The accurate analysis of each of these modalities promotes the detection of more appropriate medical decisions. Multimodal medical imaging is a research field that consists in the development of robust algorithms that can enable the fusion of image information acquired by different sets of modalities. In this paper, a novel multimodal medical image fusion algorithm is proposed for a wide range of medical diagnostic problems. It is based on the application of a boundary measured pulse-coupled neural network fusion strategy and an energy attribute fusion strategy in a non-subsampled shearlet transform domain. Our algorithm was validated in dataset with modalities of several diseases, namely glioma, Alzheimer’s, and metastatic bronchogenic carcinoma, which contain more than 100 image pairs. Qualitative and quantitative evaluation verifies that the proposed algorithm outperforms most of the current algorithms, providing important ideas for medical diagnosis." @default.
- W3040984225 created "2020-07-16" @default.
- W3040984225 creator A5017217950 @default.
- W3040984225 creator A5027004576 @default.
- W3040984225 creator A5050410519 @default.
- W3040984225 creator A5063338644 @default.
- W3040984225 creator A5082046789 @default.
- W3040984225 date "2020-07-08" @default.
- W3040984225 modified "2023-10-12" @default.
- W3040984225 title "Multimodal medical image fusion algorithm in the era of big data" @default.
- W3040984225 cites W1986517950 @default.
- W3040984225 cites W2025133197 @default.
- W3040984225 cites W2039608780 @default.
- W3040984225 cites W2043359668 @default.
- W3040984225 cites W2054273865 @default.
- W3040984225 cites W2097061348 @default.
- W3040984225 cites W2103504761 @default.
- W3040984225 cites W2156483112 @default.
- W3040984225 cites W2179019672 @default.
- W3040984225 cites W2411377185 @default.
- W3040984225 cites W2474462684 @default.
- W3040984225 cites W2522703671 @default.
- W3040984225 cites W2536011999 @default.
- W3040984225 cites W2623678757 @default.
- W3040984225 cites W2744198280 @default.
- W3040984225 cites W2746410086 @default.
- W3040984225 cites W2766229547 @default.
- W3040984225 cites W2766827431 @default.
- W3040984225 cites W2774641008 @default.
- W3040984225 cites W2785521508 @default.
- W3040984225 cites W2800278510 @default.
- W3040984225 cites W2808591023 @default.
- W3040984225 cites W2891686988 @default.
- W3040984225 cites W2897040237 @default.
- W3040984225 cites W2898653582 @default.
- W3040984225 cites W2902228322 @default.
- W3040984225 cites W2904188817 @default.
- W3040984225 cites W2912551047 @default.
- W3040984225 cites W2912581987 @default.
- W3040984225 cites W2915813489 @default.
- W3040984225 cites W2916345110 @default.
- W3040984225 cites W2921384086 @default.
- W3040984225 cites W2922968028 @default.
- W3040984225 cites W2931071678 @default.
- W3040984225 cites W2936534246 @default.
- W3040984225 cites W2936775474 @default.
- W3040984225 cites W2948666538 @default.
- W3040984225 cites W2971978647 @default.
- W3040984225 cites W2972609628 @default.
- W3040984225 cites W2977354825 @default.
- W3040984225 cites W2986631711 @default.
- W3040984225 cites W2993853848 @default.
- W3040984225 cites W2998957378 @default.
- W3040984225 cites W2999333317 @default.
- W3040984225 cites W3004181560 @default.
- W3040984225 cites W3006740354 @default.
- W3040984225 cites W3006740421 @default.
- W3040984225 cites W3014217142 @default.
- W3040984225 cites W3014401456 @default.
- W3040984225 cites W3016247515 @default.
- W3040984225 doi "https://doi.org/10.1007/s00521-020-05173-2" @default.
- W3040984225 hasPublicationYear "2020" @default.
- W3040984225 type Work @default.
- W3040984225 sameAs 3040984225 @default.
- W3040984225 citedByCount "58" @default.
- W3040984225 countsByYear W30409842252020 @default.
- W3040984225 countsByYear W30409842252021 @default.
- W3040984225 countsByYear W30409842252022 @default.
- W3040984225 countsByYear W30409842252023 @default.
- W3040984225 crossrefType "journal-article" @default.
- W3040984225 hasAuthorship W3040984225A5017217950 @default.
- W3040984225 hasAuthorship W3040984225A5027004576 @default.
- W3040984225 hasAuthorship W3040984225A5050410519 @default.
- W3040984225 hasAuthorship W3040984225A5063338644 @default.
- W3040984225 hasAuthorship W3040984225A5082046789 @default.
- W3040984225 hasBestOaLocation W30409842251 @default.
- W3040984225 hasConcept C11413529 @default.
- W3040984225 hasConcept C115961682 @default.
- W3040984225 hasConcept C119857082 @default.
- W3040984225 hasConcept C126838900 @default.
- W3040984225 hasConcept C134306372 @default.
- W3040984225 hasConcept C138885662 @default.
- W3040984225 hasConcept C144024400 @default.
- W3040984225 hasConcept C153180895 @default.
- W3040984225 hasConcept C154945302 @default.
- W3040984225 hasConcept C202444582 @default.
- W3040984225 hasConcept C2776401178 @default.
- W3040984225 hasConcept C2779903281 @default.
- W3040984225 hasConcept C2780226545 @default.
- W3040984225 hasConcept C31601959 @default.
- W3040984225 hasConcept C33923547 @default.
- W3040984225 hasConcept C36289849 @default.
- W3040984225 hasConcept C36503486 @default.
- W3040984225 hasConcept C41008148 @default.
- W3040984225 hasConcept C41895202 @default.
- W3040984225 hasConcept C534262118 @default.
- W3040984225 hasConcept C69744172 @default.
- W3040984225 hasConcept C71924100 @default.
- W3040984225 hasConcept C9652623 @default.
- W3040984225 hasConceptScore W3040984225C11413529 @default.