Matches in SemOpenAlex for { <https://semopenalex.org/work/W4226530565> ?p ?o ?g. }
- W4226530565 endingPage "1467" @default.
- W4226530565 startingPage "1454" @default.
- W4226530565 abstract "In this paper, we present a deep learning method, DDMReg, for accurate registration between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align brain anatomical structures while ensuring that local fiber orientations remain consistent with the underlying white matter fiber tract anatomy. DDMReg is a novel method that uses joint whole-brain and tract-specific information for dMRI registration. Based on the successful VoxelMorph framework for image registration, we propose a novel registration architecture that leverages not only whole brain information but also tract-specific fiber orientation information. DDMReg is an unsupervised method for deformable registration between pairs of dMRI datasets: it does not require nonlinearly pre-registered training data or the corresponding deformation fields as ground truth. We perform comparisons with four state-of-the-art registration methods on multiple independently acquired datasets from different populations (including teenagers, young and elderly adults) and different imaging protocols and scanners. We evaluate the registration performance by assessing the ability to align anatomically corresponding brain structures and ensure fiber spatial agreement between different subjects after registration. Experimental results show that DDMReg obtains significantly improved registration performance compared to the state-of-the-art methods. Importantly, we demonstrate successful generalization of DDMReg to dMRI data from different populations with varying ages and acquired using different acquisition protocols and different scanners." @default.
- W4226530565 created "2022-05-05" @default.
- W4226530565 creator A5021319515 @default.
- W4226530565 creator A5053447705 @default.
- W4226530565 creator A5082042615 @default.
- W4226530565 date "2022-06-01" @default.
- W4226530565 modified "2023-10-15" @default.
- W4226530565 title "Deep Diffusion MRI Registration (DDMReg): A Deep Learning Method for Diffusion MRI Registration" @default.
- W4226530565 cites W1526085390 @default.
- W4226530565 cites W1555823621 @default.
- W4226530565 cites W1760021997 @default.
- W4226530565 cites W1875854697 @default.
- W4226530565 cites W1948855311 @default.
- W4226530565 cites W1964802316 @default.
- W4226530565 cites W1965894642 @default.
- W4226530565 cites W1967301131 @default.
- W4226530565 cites W1970928383 @default.
- W4226530565 cites W1983208069 @default.
- W4226530565 cites W1985108458 @default.
- W4226530565 cites W1985308456 @default.
- W4226530565 cites W1987869189 @default.
- W4226530565 cites W1988494453 @default.
- W4226530565 cites W1997244362 @default.
- W4226530565 cites W1997339620 @default.
- W4226530565 cites W2030669466 @default.
- W4226530565 cites W2048083280 @default.
- W4226530565 cites W2071163824 @default.
- W4226530565 cites W2073111135 @default.
- W4226530565 cites W2075047855 @default.
- W4226530565 cites W2077240096 @default.
- W4226530565 cites W2091910928 @default.
- W4226530565 cites W2094682431 @default.
- W4226530565 cites W2097047986 @default.
- W4226530565 cites W2098452910 @default.
- W4226530565 cites W2102099319 @default.
- W4226530565 cites W2113576511 @default.
- W4226530565 cites W2113998344 @default.
- W4226530565 cites W2114856020 @default.
- W4226530565 cites W2115144214 @default.
- W4226530565 cites W2115167851 @default.
- W4226530565 cites W2117290619 @default.
- W4226530565 cites W2135354879 @default.
- W4226530565 cites W2137679584 @default.
- W4226530565 cites W2138144081 @default.
- W4226530565 cites W2142900310 @default.
- W4226530565 cites W2144314866 @default.
- W4226530565 cites W2145138920 @default.
- W4226530565 cites W2150667092 @default.
- W4226530565 cites W2155298532 @default.
- W4226530565 cites W2157035009 @default.
- W4226530565 cites W2158402095 @default.
- W4226530565 cites W241994552 @default.
- W4226530565 cites W2498672755 @default.
- W4226530565 cites W2559388217 @default.
- W4226530565 cites W2579154168 @default.
- W4226530565 cites W2766098209 @default.
- W4226530565 cites W2766639217 @default.
- W4226530565 cites W2770351665 @default.
- W4226530565 cites W2783229927 @default.
- W4226530565 cites W2789530810 @default.
- W4226530565 cites W2789758093 @default.
- W4226530565 cites W2803837136 @default.
- W4226530565 cites W2803890652 @default.
- W4226530565 cites W2808875895 @default.
- W4226530565 cites W2816936748 @default.
- W4226530565 cites W2885873321 @default.
- W4226530565 cites W2912944597 @default.
- W4226530565 cites W2921302667 @default.
- W4226530565 cites W2946440603 @default.
- W4226530565 cites W2966883685 @default.
- W4226530565 cites W2970898057 @default.
- W4226530565 cites W2972389188 @default.
- W4226530565 cites W2972997093 @default.
- W4226530565 cites W2977883299 @default.
- W4226530565 cites W2980226202 @default.
- W4226530565 cites W3010920151 @default.
- W4226530565 cites W3011855205 @default.
- W4226530565 cites W3013056581 @default.
- W4226530565 cites W3013280574 @default.
- W4226530565 cites W3018854579 @default.
- W4226530565 cites W3024316311 @default.
- W4226530565 cites W3049002444 @default.
- W4226530565 cites W3092212736 @default.
- W4226530565 cites W3099561884 @default.
- W4226530565 cites W3103010481 @default.
- W4226530565 cites W3104164805 @default.
- W4226530565 cites W3106524252 @default.
- W4226530565 cites W3111025719 @default.
- W4226530565 cites W3112186800 @default.
- W4226530565 cites W3114062792 @default.
- W4226530565 cites W3136358712 @default.
- W4226530565 cites W3160768770 @default.
- W4226530565 cites W4251708881 @default.
- W4226530565 cites W4256536686 @default.
- W4226530565 cites W4299627282 @default.
- W4226530565 cites W88165185 @default.
- W4226530565 doi "https://doi.org/10.1109/tmi.2021.3139507" @default.
- W4226530565 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34968177" @default.