Fig 2 -

<p>Block diagrams of Proposed Methods 1 and 2: ‘A’ presents the block diagram of Proposed Method 1 i.e. KI-Net. In this method, composite images obtained through adaptive coil combination from N receiver coils’ VD under-sampled images are fed into K-Net. K-Net generates interpolated composite...

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Bibliographic Details
Main Author:	Madiha Arshad (20542711) (author)
Other Authors:	Faisal Najeeb (20542714) (author), Rameesha Khawaja (20542717) (author), Amna Ammar (20542720) (author), Kashif Amjad (7665488) (author), Hammad Omer (17412783) (author)
Published:	2025
Subjects:	Cell Biology Space Science Astronomical and Space Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified typically use u higher peak signal experimental results demonstrate enhance overall robustness current research focus >- space domain single domain methods coil data consistency improve image quality conventional deep learning div >< p image domain learning proposed methods outperform dual domain methods proposed hybrid dual deep learning sampled data image reconstruction variable density two categories rmse ), respiratory motion resolution applications residual artifacts reduce artifacts recovering diagnostic reconstruction process parallel imaging paper introduces often resulting noise ratio k </ incorporates multi high spatial gained attention fully exploit compressed sensing addressing cardiac
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Fig 2 -

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