FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4311442013> ?p ?o ?g. }

• W4311442013 endingPage "117" @default.
• W4311442013 startingPage "85" @default.
• W4311442013 abstract "Brain diseases, including tumors and mental and neurological disorders, seriously threaten the health and well-being of millions of people worldwide. Structural and functional neuroimaging modalities are commonly used by physicians to aid the diagnosis of brain diseases. In clinical settings, specialist doctors typically fuse the magnetic resonance imaging (MRI) data with other neuroimaging modalities for brain disease detection. As these two approaches offer complementary information, fusing these neuroimaging modalities helps physicians accurately diagnose brain diseases. Typically, fusion is performed between a functional and a structural neuroimaging modality. Because the functional modality can complement the structural modality information, thus improving the performance for the diagnosis of brain diseases by specialists. However, analyzing the fusion of neuroimaging modalities is difficult for specialist doctors. Deep Learning (DL) is a branch of artificial intelligence that has shown superior performances compared to more conventional methods in tasks such as brain disease detection from neuroimaging modalities. This work presents a comprehensive review paper in the field of brain disease detection from the fusion of neuroimaging modalities using DL models like convolutional neural networks (CNNs), recurrent neural networks (RNNs), pretrained, generative adversarial networks (GANs), and Autoencoders (AEs). First, neuroimaging modalities and the need for fusion are discussed. Then, review papers published in the field of neuroimaging multimodalities using AI techniques are explored. Moreover, fusion levels based on DL methods, including input, layer, and decision, with related studies conducted on diagnosing brain diseases, are discussed. Other sections present the most important challenges for diagnosing brain diseases from the fusion of neuroimaging modalities. In the discussion section, the details of previous research on the fusion of neuroimaging modalities based on MRI and DL models are reported. In the following, the most important future directions include Datasets, DA, imbalanced data, DL models, explainable AI, and hardware resources are presented. Finally, the main findings of this study are presented in the conclusion section." @default.
• W4311442013 created "2022-12-26" @default.
• W4311442013 creator A5011354002 @default.
• W4311442013 creator A5016211231 @default.
• W4311442013 creator A5019852514 @default.
• W4311442013 creator A5020189322 @default.
• W4311442013 creator A5021720735 @default.
• W4311442013 creator A5026100921 @default.
• W4311442013 creator A5029791697 @default.
• W4311442013 creator A5033333265 @default.
• W4311442013 creator A5043378483 @default.
• W4311442013 creator A5047925214 @default.
• W4311442013 creator A5048673267 @default.
• W4311442013 creator A5059557438 @default.
• W4311442013 creator A5071968752 @default.
• W4311442013 creator A5079852457 @default.
• W4311442013 creator A5088569839 @default.
• W4311442013 date "2023-05-01" @default.
• W4311442013 modified "2023-10-18" @default.
• W4311442013 title "Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review" @default.
• W4311442013 cites W1519835194 @default.
• W4311442013 cites W1559104216 @default.
• W4311442013 cites W1849775727 @default.
• W4311442013 cites W1983404333 @default.
• W4311442013 cites W1986287200 @default.
• W4311442013 cites W1995250682 @default.
• W4311442013 cites W1996532015 @default.
• W4311442013 cites W1996972343 @default.
• W4311442013 cites W1997974370 @default.
• W4311442013 cites W1998525351 @default.
• W4311442013 cites W2002171347 @default.
• W4311442013 cites W2006931708 @default.
• W4311442013 cites W2014022174 @default.
• W4311442013 cites W2015452969 @default.
• W4311442013 cites W2019140380 @default.
• W4311442013 cites W2030535407 @default.
• W4311442013 cites W2038910549 @default.
• W4311442013 cites W2048901171 @default.
• W4311442013 cites W2051331044 @default.
• W4311442013 cites W2056327529 @default.
• W4311442013 cites W2064366277 @default.
• W4311442013 cites W2065437875 @default.
• W4311442013 cites W2066667210 @default.
• W4311442013 cites W2072522618 @default.
• W4311442013 cites W2072776687 @default.
• W4311442013 cites W2073533288 @default.
• W4311442013 cites W2077010356 @default.
• W4311442013 cites W2077164692 @default.
• W4311442013 cites W2082526668 @default.
• W4311442013 cites W2120259577 @default.
• W4311442013 cites W2120408841 @default.
• W4311442013 cites W2128390591 @default.
• W4311442013 cites W2133665775 @default.
• W4311442013 cites W2135380777 @default.
• W4311442013 cites W2160218787 @default.
• W4311442013 cites W2171251197 @default.
• W4311442013 cites W2227017970 @default.
• W4311442013 cites W2273013813 @default.
• W4311442013 cites W2292862470 @default.
• W4311442013 cites W2411377185 @default.
• W4311442013 cites W2574038793 @default.
• W4311442013 cites W2583640209 @default.
• W4311442013 cites W2604527018 @default.
• W4311442013 cites W2617148768 @default.
• W4311442013 cites W2624240493 @default.
• W4311442013 cites W2729145866 @default.
• W4311442013 cites W2744019306 @default.
• W4311442013 cites W2762517398 @default.
• W4311442013 cites W2765811365 @default.
• W4311442013 cites W2767290858 @default.
• W4311442013 cites W2777760371 @default.
• W4311442013 cites W2788093030 @default.
• W4311442013 cites W2791155853 @default.
• W4311442013 cites W2791282053 @default.
• W4311442013 cites W2791822495 @default.
• W4311442013 cites W2791983077 @default.
• W4311442013 cites W2792023360 @default.
• W4311442013 cites W2792193061 @default.
• W4311442013 cites W2798869704 @default.
• W4311442013 cites W2810024032 @default.
• W4311442013 cites W2810658548 @default.
• W4311442013 cites W2883420106 @default.
• W4311442013 cites W2891118631 @default.
• W4311442013 cites W2893063021 @default.
• W4311442013 cites W2897906330 @default.
• W4311442013 cites W2899335103 @default.
• W4311442013 cites W2902390233 @default.
• W4311442013 cites W2902972155 @default.
• W4311442013 cites W2903356598 @default.
• W4311442013 cites W2907760128 @default.
• W4311442013 cites W2910860267 @default.
• W4311442013 cites W2914139557 @default.
• W4311442013 cites W2915335211 @default.
• W4311442013 cites W2916257687 @default.
• W4311442013 cites W2918930673 @default.
• W4311442013 cites W2926425062 @default.
• W4311442013 cites W2936503027 @default.
• W4311442013 cites W2941458854 @default.

• next