Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Monami Banerjee"'
Publikováno v:
PLoS ONE, Vol 11, Iss 6, p e0155764 (2016)
Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder that affects patients in all countries and of all nationalities. Magnetic resonance imaging (MRI) is currently one of the most widely used diagnostic imaging techniques
Externí odkaz:
https://doaj.org/article/76f2f1f634e04dabaf790a75ab305c61
Autor:
David D. Fuller, Jiaqi Sun, Baba C. Vemuri, Monami Banerjee, Sara M.F. Turner, Zhixin Pan, John R. Forder, Alireza Entezari
Publikováno v:
Medical Image Analysis. 57:89-105
Diffusion-weighted magnetic resonance imaging (dMRI) is a non-invasive technique to probe the complex micro-architecture of the tissue being imaged. The diffusional properties of the tissue at the imaged resolution are well captured by the ensemble a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6ae983778297b1d72b6051858710366
https://doi.org/10.1016/j.media.2019.06.012
https://doi.org/10.1016/j.media.2019.06.012
Convolutional neural networks have been highly successful in image-based learning tasks due to their translation equivariance property. Recent work has generalized the traditional convolutional layer of a convolutional neural network to non-Euclidean
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9d1d2f4ff116cc5b2027b67bd651538
http://arxiv.org/abs/2106.15301
http://arxiv.org/abs/2106.15301
Autor:
Jorge S Reis-Filho, Fresia Pareja, Fatemeh Derakhshan, David N Brown, Jillian Sue, Pier Selenica, Yi Kan Wang, Arnaud Da Cruz Paula, Monami Banerjee, Zahra Ebrahimzadeh, Manuel Isava, Matthew Lee, Ran Godrich, Adam Casson, Ruben Padron, George Shaikovski, Alexander van Eck, Antonio Marra, Higinio Dopeso, Hannah Y Wen, Edi Brogi, Matthew G Hanna, Chris Kanan, Jeremy D Kunz, Felipe C Geyer, Carla Leibowitz, David Klimstra, Leo Grady, Thomas J Fuchs
Publikováno v:
Cancer Research. 82:PD11-01
Introduction: Invasive lobular carcinoma (ILC) is the most frequent special histologic subtype of breast cancer (BC). ILC is identifiable by pathologic assessment given its distinctive discohesive growth pattern, largely caused by CDH1 inactivation.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fad2afbb2215569c6c9841459630ac5f
https://doi.org/10.1158/1538-7445.sabcs21-pd11-01
https://doi.org/10.1158/1538-7445.sabcs21-pd11-01
Autor:
Baba C. Vemuri, Monami Banerjee, Rudrasis Chakraborty, Derek B. Archer, David E. Vaillancourt
Publikováno v:
ISBI
Convolutional neural networks are ubiquitous in Machine Learning applications for solving a variety of problems. They however can not be used in their native form when the domain of the data is commonly encountered manifolds such as the sphere, the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e10cdcad29638bbdedd26d0a0c93582
https://doi.org/10.1109/isbi.2019.8759558
https://doi.org/10.1109/isbi.2019.8759558
Autor:
Nikhil R. Pal, Monami Banerjee
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 27:3390-3403
Features selected by a supervised/ unsupervised technique often include redundant or correlated features. While use of correlated features may result in an increase in the design and decision making cost, removing redundancy completely can make the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4bda20907f7e49a81cb1c5f3e6ce7d8
https://doi.org/10.1109/tkde.2015.2455509
https://doi.org/10.1109/tkde.2015.2455509
Publikováno v:
ICCV
Principal Component Analysis (PCA) is a widely popular dimensionality reduction technique for vector-valued inputs. In the past decade, a nonlinear generalization of PCA, called the Principal Geodesic Analysis (PGA) was developed to tackle data that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f310dfd2f45f17c00317dc6237486c56
https://doi.org/10.1109/iccv.2017.536
https://doi.org/10.1109/iccv.2017.536
Publikováno v:
ISBI
Statistical analysis of longitudinal data is a significant problem in Biomedical imaging applications. In the recent past, several researchers have developed mathematically rigorous methods based on differential geometry and statistics to tackle the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e66068c2c7baec9656ddff0b8b1cfa49
https://doi.org/10.1109/isbi.2017.7950684
https://doi.org/10.1109/isbi.2017.7950684
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319590493
IPMI
IPMI
In this paper, we present novel algorithms to compute robust statistics from manifold-valued data. Specifically, we present algorithms for estimating the robust Frechet Mean (FM) and performing a robust exact-principal geodesic analysis (ePGA) for da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40d2d1d7faf81777744f47afa0f7d0cd
https://doi.org/10.1007/978-3-319-59050-9_1
https://doi.org/10.1007/978-3-319-59050-9_1
Autor:
Nikhil R. Pal, Monami Banerjee
Publikováno v:
Information Sciences. 264:118-134
Many approaches have been developed for dimensionality reduction. These approaches can broadly be categorized into supervised and unsupervised methods. In case of supervised dimensionality reduction, for any input vector the target value is known, wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ecbc5fc2db6ec44467a06d467a3742ee
https://doi.org/10.1016/j.ins.2013.12.029
https://doi.org/10.1016/j.ins.2013.12.029