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11 results on '"Errico, Rosangela"'

1. Feature Selection based on Machine Learning in MRIs for Hippocampal Segmentation

Author

Tangaro, Sabina, Amoroso, Nicola, Brescia, Massimo, Cavuoti, Stefano, Chincarini, Andrea, Errico, Rosangela, Inglese, Paolo, Longo, Giuseppe, Maglietta, Rosalia, Tateo, Andrea, Riccio, Giuseppe, and Bellotti, Roberto

Subjects
Physics - Medical Physics, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Learning
Abstract

Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic Resonance Imaging (MRI) scans can show these variations and therefore be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach, for each voxel a number of local features were calculated. In this paper we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) Sequential Forward Selection and (iii) Sequential Backward Elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 features for each voxel (sequential backward elimination) we obtained comparable state of-the-art performances with respect to the standard tool FreeSurfer., Comment: To appear on "Computational and Mathematical Methods in Medicine", Hindawi Publishing Corporation. 19 pages, 7 figures

Published
2015
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2. Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Author

Allen, Genevera I, Amoroso, Nicola, Anghel, Catalina, Balagurusamy, Venkat, Bare, Christopher J, Beaton, Derek, Bellotti, Roberto, Bennett, David A, Boehme, Kevin L, Boutros, Paul C, Caberlotto, Laura, Caloian, Cristian, Campbell, Frederick, Neto, Elias Chaibub, Chang, Yu‐Chuan, Chen, Beibei, Chen, Chien‐Yu, Chien, Ting‐Ying, Clark, Tim, Das, Sudeshna, Davatzikos, Christos, Deng, Jieyao, Dillenberger, Donna, Dobson, Richard JB, Dong, Qilin, Doshi, Jimit, Duma, Denise, Errico, Rosangela, Erus, Guray, Everett, Evan, Fardo, David W, Friend, Stephen H, Fröhlich, Holger, Gan, Jessica, St George‐Hyslop, Peter, Ghosh, Satrajit S, Glaab, Enrico, Green, Robert C, Guan, Yuanfang, Hong, Ming‐Yi, Huang, Chao, Hwang, Jinseub, Ibrahim, Joseph, Inglese, Paolo, Iyappan, Anandhi, Jiang, Qijia, Katsumata, Yuriko, Kauwe, John SK, Klein, Arno, Kong, Dehan, Krause, Roland, Lalonde, Emilie, Lauria, Mario, Lee, Eunjee, Lin, Xihui, Liu, Zhandong, Livingstone, Julie, Logsdon, Benjamin A, Lovestone, Simon, Ma, Tsung‐wei, Malhotra, Ashutosh, Mangravite, Lara M, Maxwell, Taylor J, Merrill, Emily, Nagorski, John, Namasivayam, Aishwarya, Narayan, Manjari, Naz, Mufassra, Newhouse, Stephen J, Norman, Thea C, Nurtdinov, Ramil N, Oyang, Yen‐Jen, Pawitan, Yudi, Peng, Shengwen, Peters, Mette A, Piccolo, Stephen R, Praveen, Paurush, Priami, Corrado, Sabelnykova, Veronica Y, Senger, Philipp, Shen, Xia, Simmons, Andrew, Sotiras, Aristeidis, Stolovitzky, Gustavo, Tangaro, Sabina, Tateo, Andrea, Tung, Yi‐An, Tustison, Nicholas J, Varol, Erdem, Vradenburg, George, Weiner, Michael W, Xiao, Guanghua, Xie, Lei, Xie, Yang, Xu, Jia, Yang, Hojin, Zhan, Xiaowei, Zhou, Yunyun, Zhu, Fan, and Zhu, Hongtu

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Acquired Cognitive Impairment, Prevention, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Alzheimer's Disease, Aging, Brain Disorders, Neurological, Alzheimer Disease, Apolipoproteins E, Biomarkers, Cognition Disorders, Computational Biology, Databases, Bibliographic, Humans, Predictive Value of Tests, Azheimer's disease, Crowdsource, Big data, Bioinformatics, Cognitive decline, Imaging, Genetics, Alzheimer's Disease Neuroimaging Initiative, Geriatrics, Clinical sciences, Biological psychology
Abstract

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.

Published
2016

5. An Hippocampal Segmentation Tool Within an Open Cloud Infrastructure

Author

Amoroso, Nicola, Tangaro, Sabina, Errico, Rosangela, Garuccio, Elena, Monda, Anna, Sensi, Francesco, Tateo, Andrea, Bellotti, Roberto, Initiative, [Authorinst]for the Alzheimer’s Disease Neuroimaging, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Murino, Vittorio, editor, Puppo, Enrico, editor, Sona, Diego, editor, Cristani, Marco, editor, and Sansone, Carlo, editor

Published
2015
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7. Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group) [research center], Fonds National de la Recherche - FnR [sponsor], Allen, Genevera, Amoroso, Nicola, Anghel, Catalina, Balagurusamy, Venkat, Bare, Christopher, Beaton, Derek, Bellotti, Roberto, Bennett, David, Boehme, Kevin, Caberlotto, Laura, Campbell, Frederick, Chang, Yu-Chuan, Chen, Beibei, Chen, Chien-Yu, Chien, Ting-Ying, Clark, Tim, Das, Sudeshna, Davatzikos, Christos, Deng, Jieyao, Dillenberger, Donna, Dobson, Richard, Dong, Qilin, Doshi, Jimit, Duma, Denise, Errico, Rosangela, Erus, Guray, Everett, Evan, Fardo, David, Friend, Stephen, Fröhlich, Holger, Gan, Jessica, St George-Hyslop, Peter, Ghosh, Satrajit, Glaab, Enrico, Green, Robert, Guan, Yuanfang, Hong, Ming-Yi, Huang, Chao, Hwang, Jinseub, Ibrahim, Joseph, Inglese, Paolo, Jiang, Qijia, Katsumata, Yurik, Kauwe, Jo, Klein, Arno, Kong, Dehan, Krause, Roland, Lalonde, Emilie, Lauria, Mari, Lee, Eunjee, Lin, Xihui, Liu, Zhandong, Livingstone, Julie, Logsdon, Benjami, Lovestone, Simon, Iyappan, Anandhi, Ma, Tsung-wei, Malhotra, Ashutos, Maxwell, Taylor, Merrill, Emily, Nagorski, John, Alex Namasivayam, Aishwarya, Narayan, Manjari, Naz, Mufassra, Neto, Elias Chaibub, Newhouse, Stephen, Norman, Thea, Nurtdinov, Ramil, Oyang, Yen-Jen, Boutros, Paul, Pawitan, Yudi, Peng, Shengwen, Peters, Mette, Piccolo, Stephen, Praveen, Paurush, Priami, Corrado, Sabelnykova, Veronica, Senger, Philipp, Shen, Xia, Simmons, Andrew, Sotiras, Aristeidis, Stolovitzky, Gustavo, Tangaro, Sabina, Tateo, Andrea, Tung, Yi-An, Tustison, Nicholas, Varol, Erdem, Vradenburg, George, Weiner, Michael, Xiao, Guanghua, Xie, Lei, Xie, Yang, Xu, Jia, Yang, Hojin, Zhan, Xiaowei, Zhou, Yunyun, Zhu, Fan, Zhu, Hongtu, Zhu, Shanfeng, Alzheimer's Disease Neuroimaging Initiative, Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group) [research center], Fonds National de la Recherche - FnR [sponsor], Allen, Genevera, Amoroso, Nicola, Anghel, Catalina, Balagurusamy, Venkat, Bare, Christopher, Beaton, Derek, Bellotti, Roberto, Bennett, David, Boehme, Kevin, Caberlotto, Laura, Campbell, Frederick, Chang, Yu-Chuan, Chen, Beibei, Chen, Chien-Yu, Chien, Ting-Ying, Clark, Tim, Das, Sudeshna, Davatzikos, Christos, Deng, Jieyao, Dillenberger, Donna, Dobson, Richard, Dong, Qilin, Doshi, Jimit, Duma, Denise, Errico, Rosangela, Erus, Guray, Everett, Evan, Fardo, David, Friend, Stephen, Fröhlich, Holger, Gan, Jessica, St George-Hyslop, Peter, Ghosh, Satrajit, Glaab, Enrico, Green, Robert, Guan, Yuanfang, Hong, Ming-Yi, Huang, Chao, Hwang, Jinseub, Ibrahim, Joseph, Inglese, Paolo, Jiang, Qijia, Katsumata, Yurik, Kauwe, Jo, Klein, Arno, Kong, Dehan, Krause, Roland, Lalonde, Emilie, Lauria, Mari, Lee, Eunjee, Lin, Xihui, Liu, Zhandong, Livingstone, Julie, Logsdon, Benjami, Lovestone, Simon, Iyappan, Anandhi, Ma, Tsung-wei, Malhotra, Ashutos, Maxwell, Taylor, Merrill, Emily, Nagorski, John, Alex Namasivayam, Aishwarya, Narayan, Manjari, Naz, Mufassra, Neto, Elias Chaibub, Newhouse, Stephen, Norman, Thea, Nurtdinov, Ramil, Oyang, Yen-Jen, Boutros, Paul, Pawitan, Yudi, Peng, Shengwen, Peters, Mette, Piccolo, Stephen, Praveen, Paurush, Priami, Corrado, Sabelnykova, Veronica, Senger, Philipp, Shen, Xia, Simmons, Andrew, Sotiras, Aristeidis, Stolovitzky, Gustavo, Tangaro, Sabina, Tateo, Andrea, Tung, Yi-An, Tustison, Nicholas, Varol, Erdem, Vradenburg, George, Weiner, Michael, Xiao, Guanghua, Xie, Lei, Xie, Yang, Xu, Jia, Yang, Hojin, Zhan, Xiaowei, Zhou, Yunyun, Zhu, Fan, Zhu, Hongtu, Zhu, Shanfeng, and Alzheimer's Disease Neuroimaging Initiative

Published
2016

10. Feature Selection Based on Machine Learning in MRIs for Hippocampal Segmentation

Author

Tangaro, Sabina, primary, Amoroso, Nicola, additional, Brescia, Massimo, additional, Cavuoti, Stefano, additional, Chincarini, Andrea, additional, Errico, Rosangela, additional, Inglese, Paolo, additional, Longo, Giuseppe, additional, Maglietta, Rosalia, additional, Tateo, Andrea, additional, Riccio, Giuseppe, additional, and Bellotti, Roberto, additional

Published
2015
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11. Feature Selection Based on Machine Learning in MRIs for Hippocampal Segmentation

Author

Roberto Bellotti, Massimo Brescia, Rosalia Maglietta, Rosangela Errico, Nicola Amoroso, Paolo Inglese, Stefano Cavuoti, Giuseppe Longo, Giuseppe Riccio, Sabina Tangaro, Andrea Chincarini, Andrea Tateo, Tangaro, Sabina, Amoroso, N., Brescia, M., Cavuoti, S., Chincarini, A., Errico, R., Inglese, P., Longo, G., Maglietta, R., Tateo, A., Riccio, G., Bellotti, R., Amoroso, Nicola, Brescia, Massimo, Cavuoti, Stefano, Chincarini, Andrea, Errico, Rosangela, Paolo, Inglese, Longo, Giuseppe, Maglietta, Rosalia, Tateo, Andrea, Riccio, Giuseppe, Bellotti, Roberto, and ITA

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Computer science, Computer Vision and Pattern Recognition (cs.CV), Physics - Medical Physic, Computer Science - Computer Vision and Pattern Recognition, computer.software_genre, Hippocampus, Machine Learning (cs.LG), Pattern Recognition, Automated, Machine Learning, Voxel, Image Processing, Computer-Assisted, Physic, Medical Physic, medicine.diagnostic_test, Applied Mathematics, General Medicine, Magnetic Resonance Imaging, Random forest, Feature (computer vision), Modeling and Simulation, lcsh:R858-859.7, Computer Vision and Pattern Recognition, MILD COGNITIVE IMPAIRMENT, MAMMOGRAPHIC DATABASE, ALZHEIMERS-DISEASE, VALIDATION, CLASSIFICATION, MRI, Research Article, Article Subject, FOS: Physical sciences, Feature selection, lcsh:Computer applications to medicine. Medical informatics, General Biochemistry, Genetics and Molecular Biology, Set (abstract data type), medicine, Learning, Humans, General Immunology and Microbiology, business.industry, Computational Biology, Pattern recognition, Magnetic resonance imaging, Filter (signal processing), Physics - Medical Physics, Computer Science - Learning, Independent set, Computer Science, Artificial intelligence, Medical Physics (physics.med-ph), business, computer
Abstract

Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic Resonance Imaging (MRI) scans can show these variations and therefore be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach, for each voxel a number of local features were calculated. In this paper we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) Sequential Forward Selection and (iii) Sequential Backward Elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 features for each voxel (sequential backward elimination) we obtained comparable state of-the-art performances with respect to the standard tool FreeSurfer., Comment: To appear on "Computational and Mathematical Methods in Medicine", Hindawi Publishing Corporation. 19 pages, 7 figures

Published
2015

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