Search Results - "Manzanera, Octavio Martinez"

A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies by Margeta, Jan, Hussain, Raabid, López Diez, Paula, Morgenstern, Anika, Demarcy, Thomas, Wang, Zihao, Gnansia, Dan, Martinez Manzanera, Octavio, Vandersteen, Clair, Delingette, Hervé, Buechner, Andreas, Lenarz, Thomas, Patou, François, Guevara, Nicolas

“…The robust delineation of the cochlea and its inner structures combined with the detection of the electrode of a cochlear implant within these structures is…”
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Distinguishing Patients With a Coordination Disorder From Healthy Controls Using Local Features of Movement Trajectories During the Finger-to-Nose Test by Aguilar, Venustiano Soancatl, Manzanera, Octavio Martinez, Sival, Deborah A., Maurits, Natasha M., Roerdink, Jos B. T. M.

“…Assessment of coordination disorders is valuable for monitoring progression of patients, distinguishing healthy and pathological conditions, and ultimately…”
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Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment by Martinez Manzanera, Octavio, Elting, Jan Willem, van der Hoeven, Johannes H, Maurits, Natasha M

“…In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For…”
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Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson's Disease in 3D Nuclear Imaging Data by Manzanera, Octavio Martinez, Meles, Sanne K, Leenders, Klaus L, Renken, Remco J, Pagani, Marco, Arnaldi, Dario, Nobili, Flavio, Obeso, Jose, Oroz, Maria Rodriguez, Morbelli, Silvia, Maurits, Natasha M

“…Over the last years convolutional neural networks (CNNs) have shown remarkable results in different image classification tasks, including medical imaging. One…”
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Paediatric motor phenotypes in early‐onset ataxia, developmental coordination disorder, and central hypotonia by Lawerman, Tjitske F, Brandsma, Rick, Maurits, Natalia M, Martinez‐Manzanera, Octavio, Verschuuren‐Bemelmans, Corien C, Lunsing, Roelineke J, Brouwer, Oebo F, Kremer, Hubertus PH, Sival, Deborah A

“…Aims To investigate the accuracy of phenotypic early‐onset ataxia (EOA) recognition among developmental conditions, including developmental coordination…”
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Machine Learning in the Evaluation of Myocardial Ischemia Through Nuclear Cardiology by Juarez-Orozco, Luis Eduardo, Martinez-Manzanera, Octavio, Storti, Andrea Ennio, Knuuti, Juhani

“…Purpose of Review To summarize the advances achieved in the detection and characterization of myocardial ischemia and prediction of related outcomes through…”
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Deep Learning in Quantitative PET Myocardial Perfusion Imaging by Juarez-Orozco, Luis Eduardo, Martinez-Manzanera, Octavio, van der Zant, Friso M., Knol, Remco J.J., Knuuti, Juhani

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The machine learning horizon in cardiac hybrid imaging by Juarez-Orozco, Luis Eduardo, Martinez-Manzanera, Octavio, Nesterov, Sergey V., Kajander, Sami, Knuuti, Juhani

“…Background Machine learning (ML) represents a family of algorithms that has rapidly developed within the last years in a wide variety of knowledge areas. ML is…”
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Deep Learning in Quantitative PET Myocardial Perfusion Imaging: A Study on Cardiovascular Event Prediction by Juarez-Orozco, Luis Eduardo, Martinez-Manzanera, Octavio, van der Zant, Friso M., Knol, Remco J.J., Knuuti, Juhani

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Machine learning in the integration of simple variables for identifying patients with myocardial ischemia by Juarez-Orozco, Luis Eduardo, Knol, Remco J.J., Sanchez-Catasus, Carlos A., Martinez-Manzanera, Octavio, van der Zant, Friso M., Knuuti, Juhani

“…A significant number of variables are obtained when characterizing patients suspected with myocardial ischemia or at risk of MACE. Guidelines typically use a…”
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Automatic classification of gait in children with Early-Onset Ataxia or Developmental Coordination Disorder and controls using inertial sensors by Mannini, Andrea, Martinez-Manzanera, Octavio, Lawerman, Tjitske F, Trojaniello, Diana, Croce, Ugo Della, Sival, Deborah A, Maurits, Natasha M, Sabatini, Angelo Maria

“…Highlights • We used inertial sensors and a classifier to distinguish EOA and DCD during gait. • Automatic classification obtained a similar accuracy to…”
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Patient-Specific 3d Cellular Automata Nodule Growth Synthesis In Lung Cancer Without The Need Of External Data by Manzanera, Octavio E. Martinez, Ellis, Sam, Baltatzis, Vasileios, Nair, Arjun, Le Folgoc, Loic, Desai, Sujal, Glocker, Ben, Schnabel, Julia A.

“…We propose a novel patient-specific generative approach to simulate the emergence and growth of lung nodules using 3D cellular automata (CA) in computer…”
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Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT by Ellis, Sam, Manzanera, Octavio E. Martinez, Baltatzis, Vasileios, Nawaz, Ibrahim, Nair, Arjun, Folgoc, Loïc Le, Desai, Sujal, Glocker, Ben, Schnabel, Julia A

“…GANs are able to model accurately the distribution of complex, high-dimensional datasets, e.g. images. This makes high-quality GANs useful for unsupervised…”
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Is MC Dropout Bayesian? by Folgoc, Loic Le, Baltatzis, Vasileios, Desai, Sujal, Devaraj, Anand, Ellis, Sam, Manzanera, Octavio E. Martinez, Nair, Arjun, Qiu, Huaqi, Schnabel, Julia, Glocker, Ben

“…MC Dropout is a mainstream "free lunch" method in medical imaging for approximate Bayesian computations (ABC). Its appeal is to solve out-of-the-box the…”
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The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification by Baltatzis, Vasileios, Bintsi, Kyriaki-Margarita, Folgoc, Loic Le, Manzanera, Octavio E. Martinez, Ellis, Sam, Nair, Arjun, Desai, Sujal, Glocker, Ben, Schnabel, Julia A

“…Using publicly available data to determine the performance of methodological contributions is important as it facilitates reproducibility and allows scrutiny…”
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The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data by Baltatzis, Vasileios, Folgoc, Loic Le, Ellis, Sam, Manzanera, Octavio E. Martinez, Bintsi, Kyriaki-Margarita, Nair, Arjun, Desai, Sujal, Glocker, Ben, Schnabel, Julia A

“…Convolutional Neural Networks (CNNs) are widely used for image classification in a variety of fields, including medical imaging. While most studies deploy…”
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Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data by Folgoc, Loic Le, Baltatzis, Vasileios, Alansary, Amir, Desai, Sujal, Devaraj, Anand, Ellis, Sam, Manzanera, Octavio E. Martinez, Kanavati, Fahdi, Nair, Arjun, Schnabel, Julia, Glocker, Ben

“…Datasets are rarely a realistic approximation of the target population. Say, prevalence is misrepresented, image quality is above clinical standards, etc. This…”
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