Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Chelsea E. Harris"'
Publikováno v:
Medical Imaging 2023: Computer-Aided Diagnosis.
Publikováno v:
2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP).
Publikováno v:
Astrophysical Journal, vol 912, iss 1
The Astrophysical Journal, vol 912, iss 1
The Astrophysical Journal, vol 912, iss 1
The progenitors of Type Ia supernovae (SNe Ia) are debated, particularly the evolutionary state of the binary companion that donates mass to the exploding carbon-oxygen white dwarf. In previous work, we presented hydrodynamic models and optically thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2e8c233e83efd5980704a1d29b09427
http://arxiv.org/abs/2102.11885
http://arxiv.org/abs/2102.11885
Publikováno v:
Medical Imaging 2021: Computer-Aided Diagnosis.
Breast cancer is the second most common type of cancer of women in the U.S. behind skin cancer. Early detection and characterization of breast masses is critical for effective diagnosis and treatment of breast cancer. Computer-aided breast mass chara
Observations of core-collapse supernovae (CCSNe) reveal a wealth of information about the dynamics of the supernova ejecta and its composition but very little direct information about the progenitor. Constraining properties of the progenitor and the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b58118983de5476a8abcdabf2c398b2f
http://arxiv.org/abs/2102.01118
http://arxiv.org/abs/2102.01118
Publikováno v:
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine, Elsevier, 2020, 107, pp.101885. ⟨10.1016/j.artmed.2020.101885⟩
Artif Intell Med
Artificial Intelligence in Medicine, Elsevier, 2020, 107, pp.101885. ⟨10.1016/j.artmed.2020.101885⟩
Artif Intell Med
The topic of sparse representation of samples in high dimensional spaces has attracted growing interest during the past decade. In this work, we develop sparse representation-based methods for classification of clinical imaging patterns into healthy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44a342342d64fb478cccfb42323b794a
https://hal.archives-ouvertes.fr/hal-03220916
https://hal.archives-ouvertes.fr/hal-03220916
Autor:
Peter Nugent, Chelsea E. Harris
Publikováno v:
The Astrophysical Journal, vol 894, iss 2
Explaining the observed diversity of supernovae (SNe) and the physics of explosion requires knowledge of their progenitor stars, which can be obtained by constraining the circumstellar medium (CSM). Models of the SN ejecta colliding with CSM are nece
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf249941493a40d90b60e983a53113f7
https://escholarship.org/uc/item/0vd990d5
https://escholarship.org/uc/item/0vd990d5
Publikováno v:
Mathematical and Computational Oncology ISBN: 9783030645106
ISMCO
ISMCO
Breast cancer is the most common cancer among women both in developed and developing countries. Early detection and diagnosis of breast cancer may reduce its mortality and improve the quality of life. Computer-aided detection (CADx) and computer-aide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27a6f781304974eb6284afabb0c738eb
https://doi.org/10.1007/978-3-030-64511-3_4
https://doi.org/10.1007/978-3-030-64511-3_4
Autor:
Ori Fox, Peter Nugent, Assaf Horesh, Stefano Valenti, Chelsea E. Harris, Ken J. Shen, Kate Maguire, Nathaniel R. Butler, Rob Fender, Ariel Goobar, Joe Bright, Mathew Smith, Alexei V. Filippenko, Melissa L. Graham, Patrick L. Kelly
Publikováno v:
The Astrophysical Journal
Astrophysical Journal, vol 868, iss 1
The Astrophysical Journal, vol 868, iss 1
Astrophysical Journal, vol 868, iss 1
The Astrophysical Journal, vol 868, iss 1
Despite their cosmological utility, the progenitors of Type Ia supernovae (SNe Ia) are still unknown, with many efforts focused on whether accretion from a nondegenerate companion can grow a carbon-oxygen white dwarf to near the Chandrasekhar mass. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77c1faae1f052d100734b45c5021f9f0
https://ora.ox.ac.uk/objects/uuid:976213a3-427b-4186-9d2d-6b11ed14532d
https://ora.ox.ac.uk/objects/uuid:976213a3-427b-4186-9d2d-6b11ed14532d
Publikováno v:
Comput Biol Med
Rationale The topic of sparse representation of samples in high dimensional spaces has attracted growing interest during the past decade. In this work, we develop sparse representation-based methods for classification of radiological imaging patterns