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Author |
Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez |
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Title |
Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules – Intermediate Results of the RadioLung Project |
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Journal Article |
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2023 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCARS |
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IAM |
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Admin @ si @ TGM2023 |
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3830 |
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Author |
Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil |
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A benchmark for the evaluation of computational methods for bronchoscopic navigation |
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Journal Article |
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2022 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCARS |
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17 |
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1 |
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Admin @ si @ BSC2022 |
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3832 |
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Antoni Rosell; Sonia Baeza; S. Garcia-Reina; JL. Mate; Ignasi Guasch; I. Nogueira; I. Garcia-Olive; Guillermo Torres; Carles Sanchez; Debora Gil |
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Title |
EP01.05-001 Radiomics to Increase the Effectiveness of Lung Cancer Screening Programs. Radiolung Preliminary Results |
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Journal Article |
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2022 |
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Journal of Thoracic Oncology |
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JTO |
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17 |
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9 |
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S182 |
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Admin @ si @ RBG2022b |
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3834 |
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Antoni Rosell; Sonia Baeza; S. Garcia-Reina; JL. Mate; Ignasi Guasch; I. Nogueira; I. Garcia-Olive; Guillermo Torres; Carles Sanchez; Debora Gil |
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Title |
Radiomics to increase the effectiveness of lung cancer screening programs. Radiolung preliminary results. |
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Journal Article |
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2022 |
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European Respiratory Journal |
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ERJ |
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60 |
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66 |
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Admin @ si @ RBG2022c |
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3835 |
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Jose Elias Yauri; M. Lagos; H. Vega-Huerta; P. de-la-Cruz; G.L.E Maquen-Niño; E. Condor-Tinoco |
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Title |
Detection of Epileptic Seizures Based-on Channel Fusion and Transformer Network in EEG Recordings |
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Journal Article |
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Year |
2023 |
Publication |
International Journal of Advanced Computer Science and Applications |
Abbreviated Journal |
IJACSA |
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14 |
Issue |
5 |
Pages |
1067-1074 |
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Epilepsy; epilepsy detection; EEG; EEG channel fusion; convolutional neural network; self-attention |
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According to the World Health Organization, epilepsy affects more than 50 million people in the world, and specifically, 80% of them live in developing countries. Therefore, epilepsy has become among the major public issue for many governments and deserves to be engaged. Epilepsy is characterized by uncontrollable seizures in the subject due to a sudden abnormal functionality of the brain. Recurrence of epilepsy attacks change people’s lives and interferes with their daily activities. Although epilepsy has no cure, it could be mitigated with an appropriated diagnosis and medication. Usually, epilepsy diagnosis is based on the analysis of an electroencephalogram (EEG) of the patient. However, the process of searching for seizure patterns in a multichannel EEG recording is a visual demanding and time consuming task, even for experienced neurologists. Despite the recent progress in automatic recognition of epilepsy, the multichannel nature of EEG recordings still challenges current methods. In this work, a new method to detect epilepsy in multichannel EEG recordings is proposed. First, the method uses convolutions to perform channel fusion, and next, a self-attention network extracts temporal features to classify between interictal and ictal epilepsy states. The method was validated in the public CHB-MIT dataset using the k-fold cross-validation and achieved 99.74% of specificity and 99.15% of sensitivity, surpassing current approaches. |
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Admin @ si @ |
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3856 |
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Author |
Guillermo Torres; Jan Rodríguez Dueñas; Sonia Baeza; Antoni Rosell; Carles Sanchez; Debora Gil |
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Title |
Prediction of Malignancy in Lung Cancer using several strategies for the fusion of Multi-Channel Pyradiomics Images |
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Conference Article |
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Year |
2023 |
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7th Workshop on Digital Image Processing for Medical and Automotive Industry in the framework of SYNASC 2023 |
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This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level. |
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DIPMAI |
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Admin @ si @ TRB2023 |
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3926 |
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Author |
Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez |
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Title |
Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules |
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Conference Article |
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Year |
2023 |
Publication |
37th International Congress and Exhibition is organized by Computer Assisted Radiology and Surgery |
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Munich; Germany; June 2023 |
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CARS |
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IAM |
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Admin @ si @ TGR2023a |
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3950 |
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Sonia Baeza; Debora Gil; Carles Sanchez; Guillermo Torres; Ignasi Garcia Olive; Ignasi Guasch; Samuel Garcia Reina; Felipe Andreo; Jose Luis Mate; Jose Luis Vercher; Antonio Rosell |
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Title |
Biopsia virtual radiomica para el diagnóstico histológico de nódulos pulmonares – Resultados intermedios del proyecto Radiolung |
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2023 |
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SEPAR |
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Granada; Spain; June 2023 |
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Admin @ si @ BGS2023 |
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3951 |
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Debora Gil; Guillermo Torres; Carles Sanchez |
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Transforming radiomic features into radiological words |
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2023 |
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IEEE International Symposium on Biomedical Imaging |
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Cartagena de Indias; Colombia; April 2023 |
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ISBI |
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Admin @ si @ GTS2023 |
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3952 |
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Pau Cano; Debora Gil; Eva Musulen |
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Towards automatic detection of helicobacter pylori in histological samples of gastric tissue |
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2023 |
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IEEE International Symposium on Biomedical Imaging |
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Cartagena de Indias; Colombia; April 2023 |
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ISBI |
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Admin @ si @ CGM2023 |
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3953 |
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