001449726 000__ 04678cam\a2200661\i\4500
001449726 001__ 1449726
001449726 003__ OCoLC
001449726 005__ 20230310004415.0
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001449726 007__ cr\cn\nnnunnun
001449726 008__ 220925s2022\\\\sz\a\\\\o\\\\\101\0\eng\d
001449726 020__ $$a9783031172472$$q(electronic bk.)
001449726 020__ $$a3031172477$$q(electronic bk.)
001449726 020__ $$z9783031172465
001449726 020__ $$z3031172469
001449726 0247_ $$a10.1007/978-3-031-17247-2$$2doi
001449726 035__ $$aSP(OCoLC)1345579744
001449726 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCF$$dOCLCQ
001449726 049__ $$aISEA
001449726 050_4 $$aRC78.7.D53
001449726 08204 $$a006.3/1$$223/eng/20221004
001449726 1112_ $$aMLMIR (Workshop)$$n(5th :$$d2022 :$$cSingapore).
001449726 24510 $$aMachine learning for medical image reconstruction :$$b5th international workshop, MLMIR 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022 : proceedings /$$cNandinee Haq, Patricia Johnson, Andreas Maier, Chen Qin, Tobias Würfl, Jaejun Yoo (eds.).
001449726 24630 $$aMLMIR 2022
001449726 264_1 $$aCham :$$bSpringer,$$c[2022]
001449726 264_4 $$c©2022
001449726 300__ $$a1 online resource (viii, 157 pages) :$$billustrations (some color).
001449726 336__ $$atext$$btxt$$2rdacontent
001449726 337__ $$acomputer$$bc$$2rdamedia
001449726 338__ $$aonline resource$$bcr$$2rdacarrier
001449726 4901_ $$aLecture notes in computer science,$$x1611-3349 ;$$v13587
001449726 500__ $$aInternational conference proceedings.
001449726 500__ $$aIncludes author index.
001449726 5050_ $$aDeep Learning for Magnetic Resonance Imaging -- Rethinking the optimization process for self-supervised model-driven MRI reconstruction -- NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data -- Adversarial Robustness of MR Image Reconstruction under Realistic Perturbations -- High-Fidelity MRI Reconstruction with the Densely Connected Network Cascade and Feature Residual Data Consistency Priors -- Metal artifact correction MRI using multi-contrast deep neural networks for diagnosis of degenerative spinal diseases -- Segmentation-Aware MRI Reconstruction -- MRI Reconstruction with Conditional Adversarial Transformers -- Deep Learning for General Image Reconstruction- A Noise-level-aware Framework for PET Image Denoising -- DuDoTrans: Dual-Domain Transformer for Sparse-View CT Reconstruction -- Ce Wang, Kun Shang, Haimiao Zhang, Qian Li, and S. Kevin Zhou Deep Denoising Network for X-Ray Fluoroscopic Image Sequences of Moving Objects -- PP-MPI: A Deep Plug-and-Play Prior for Magnetic Particle Imaging Reconstruction -- Learning while Acquisition: Towards Active Learning Framework for Beamforming in Ultrasound Imaging -- DPDudoNet: Deep-Prior based Dual-domain Network for Low-dose Computed Tomography Reconstruction -- MTD-GAN: Multi-Task Discriminator based Generative Adversarial Networks for Low-Dose CT Denoising -- Uncertainty-Informed Bayesian PET Image Reconstruction using a Deep Image Prior.
001449726 506__ $$aAccess limited to authorized users.
001449726 520__ $$aThis book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2022, held in conjunction with MICCAI 2022, in September 2022, held in Singapore. The 15 papers presented were carefully reviewed and selected from 19 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.
001449726 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 4, 2022).
001449726 650_0 $$aDiagnostic imaging$$xData processing$$vCongresses.
001449726 650_0 $$aArtificial intelligence$$xMedical applications$$vCongresses.
001449726 650_0 $$aMachine learning$$vCongresses.
001449726 655_0 $$aElectronic books.
001449726 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001449726 655_7 $$aConference papers and proceedings.$$2lcgft
001449726 7001_ $$aHaq, Nandinee,$$eeditor.
001449726 7001_ $$aJohnson, Patricia,$$eeditor.
001449726 7001_ $$aMaier, Andreas$$q(Andreas K.),$$eeditor.
001449726 7001_ $$aQin, Chen,$$eeditor.
001449726 7001_ $$aWürfl, Tobias,$$eeditor.
001449726 7001_ $$aYoo, Jaejun,$$eeditor.
001449726 7112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(25th :$$d2022 :$$cSingapore)
001449726 77608 $$iPrint version: $$z3031172469$$z9783031172465$$w(OCoLC)1342491600
001449726 830_0 $$aLecture notes in computer science ;$$v13587.$$x1611-3349
001449726 852__ $$bebk
001449726 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-17247-2$$zOnline Access$$91397441.1
001449726 909CO $$ooai:library.usi.edu:1449726$$pGLOBAL_SET
001449726 980__ $$aBIB
001449726 980__ $$aEBOOK
001449726 982__ $$aEbook
001449726 983__ $$aOnline
001449726 994__ $$a92$$bISE