Sean I Young
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Explore the profile of Sean I Young including associated specialties, affiliations and a list of published articles.
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11
Citations
9
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Recent Articles
1.
Gopinath K, Hoopes A, Alexander D, Arnold S, Balbastre Y, Billot B, et al.
Imaging Neurosci (Camb)
. 2025 Jan;
2():1-22.
PMID: 39850547
Synthetic data have emerged as an attractive option for developing machine-learning methods in human neuroimaging, particularly in magnetic resonance imaging (MRI)-a modality where image contrast depends enormously on acquisition hardware...
2.
Abulnaga S, Dey N, Young S, Pan E, Hobgood K, Wang C, et al.
J Mach Learn Biomed Imaging
. 2024 Oct;
2(PIPPI 2022):527-546.
PMID: 39469044
Blood oxygen level dependent (BOLD) MRI time series with maternal hyperoxia can assess placental oxygenation and function. Measuring precise BOLD changes in the placenta requires accurate temporal placental segmentation and...
3.
Wang A, Karaman B, Kim H, Rosenthal J, Saluja R, Young S, et al.
IEEE Access
. 2024 Oct;
12:53277-53292.
PMID: 39421804
Interpretability for machine learning models in medical imaging (MLMI) is an important direction of research. However, there is a general sense of murkiness in what interpretability means. Why does the...
4.
Gazula H, Tregidgo H, Billot B, Balbastre Y, Williams-Ramirez J, Herisse R, et al.
Elife
. 2024 Jun;
12.
PMID: 38896568
We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our...
5.
Young S, Dalca A, Ferrante E, Golland P, Metzler C, Fischl B, et al.
IEEE Trans Pattern Anal Mach Intell
. 2023 Jul;
PP.
PMID: 37505997
Learning-based image reconstruction models, such as those based on the U-Net, require a large set of labeled images if good generalization is to be guaranteed. In some imaging domains, however,...
6.
Gazula H, Tregidgo H, Billot B, Balbastre Y, William-Ramirez J, Herisse R, et al.
bioRxiv
. 2023 Jun;
PMID: 37333251
We present open-source tools for 3D analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our tools...
7.
Young S, Balbastre Y, Dalca A, Wells W, Iglesias J, Fischl B
Biomed Image Regist (2022)
. 2022 Nov;
13386:103-115.
PMID: 36383500
In recent years, learning-based image registration methods have gradually moved away from direct supervision with target warps to instead use self-supervision, with excellent results in several registration benchmarks. These approaches...
8.
Young S, Zhe W, Taubman D, Girod B
IEEE Trans Pattern Anal Mach Intell
. 2021 May;
44(9):5700-5714.
PMID: 34048338
In this paper, we compress convolutional neural network (CNN) weights post-training via transform quantization. Previous CNN quantization techniques tend to ignore the joint statistics of weights and activations, producing sub-optimal...
9.
Young S, Girod B, Taubman D
IEEE Trans Image Process
. 2020 Apr;
PMID: 32286986
We propose the fast optical flow extractor, a filtering method that recovers artifact-free optical flow fields from HEVCcompressed video. To extract accurate optical flow fields, we form a regularized optimization...
10.
Young S, Girod B, Taubman D
IEEE Trans Image Process
. 2020 Apr;
PMID: 32286976
Recently, many fast implementations of the bilateral and the nonlocal filters were proposed based on lattice and vector quantization, e.g. clustering, in higher dimensions. However, these approaches can still be...