User profiles for "author:Enzo Battistella"
 | Battistella EnzoThe Broad Institute of MIT and Harvard Verified email at broadinstitute.org Cited by 2551 |
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie …
[HTML][HTML] Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics
Radiomics relies on the extraction of a wide variety of quantitative image-based features to
provide decision support. Magnetic resonance imaging (MRI) contributes to the …
provide decision support. Magnetic resonance imaging (MRI) contributes to the …
AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia
G Chassagnon, M Vakalopoulou, E Battistella… - Medical image …, 2021 - Elsevier
Abstract Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around
the world rapidly. Computed tomography (CT) imaging has been proven to be an important …
the world rapidly. Computed tomography (CT) imaging has been proven to be an important …
Weakly supervised multiple instance learning histopathological tumor segmentation
Histopathological image segmentation is a challenging and important topic in medical
imaging with tremendous potential impact in clinical practice. State of the art methods rely on …
imaging with tremendous potential impact in clinical practice. State of the art methods rely on …
[HTML][HTML] Radiomics to predict outcomes and abscopal response of patients with cancer treated with immunotherapy combined with radiotherapy using a validated …
Background Combining radiotherapy (RT) with immuno-oncology (IO) therapy (IORT) may
enhance IO-induced antitumor response. Quantitative imaging biomarkers can be used to …
enhance IO-induced antitumor response. Quantitative imaging biomarkers can be used to …
[HTML][HTML] Deep learning-based concurrent brain registration and tumor segmentation
Image registration and segmentation are the two most studied problems in medical image
analysis. Deep learning algorithms have recently gained a lot of attention due to their …
analysis. Deep learning algorithms have recently gained a lot of attention due to their …
Using chest computed tomography and unsupervised machine learning for predicting and evaluating response to lumacaftor–ivacaftor in people with cystic fibrosis
A Campredon, E Battistella, C Martin… - European …, 2022 - Eur Respiratory Soc
Objectives Lumacaftor–ivacaftor is a cystic fibrosis transmembrane conductance regulator
(CFTR) modulator known to improve clinical status in people with cystic fibrosis (CF). The …
(CFTR) modulator known to improve clinical status in people with cystic fibrosis (CF). The …
Context aware 3D CNNs for brain tumor segmentation
In this work we propose a novel deep learning based pipeline for the task of brain tumor
segmentation. Our pipeline consists of three primary components:(i) a preprocessing stage …
segmentation. Our pipeline consists of three primary components:(i) a preprocessing stage …
AI-driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia
G Chassagnon, M Vakalopoulou, E Battistella… - arXiv preprint arXiv …, 2020 - arxiv.org
Chest computed tomography (CT) is widely used for the management of Coronavirus
disease 2019 (COVID-19) pneumonia because of its availability and rapidity. The standard …
disease 2019 (COVID-19) pneumonia because of its availability and rapidity. The standard …
Dosimetry-driven quality measure of brain pseudo computed tomography generated from deep learning for MRI-only radiation therapy treatment planning
EA Andres, L Fidon, M Vakalopoulou… - International Journal of …, 2020 - Elsevier
Purpose This study aims to evaluate the impact of key parameters on the pseudo computed
tomography (pCT) quality generated from magnetic resonance imaging (MRI) with a 3 …
tomography (pCT) quality generated from magnetic resonance imaging (MRI) with a 3 …