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Sonia Baeza; Debora Gil; I.Garcia Olive; M.Salcedo; J.Deportos; Carles Sanchez; Guillermo Torres; G.Moragas; Antoni Rosell |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
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Title |
A novel intelligent radiomic analysis of perfusion SPECT/CT images to optimize pulmonary embolism diagnosis in COVID-19 patients |
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Journal Article |
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2022 |
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EJNMMI Physics |
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EJNMMI-PHYS |
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9 |
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1, Article 84 |
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1-17 |
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Background: COVID-19 infection, especially in cases with pneumonia, is associated with a high rate of pulmonary embolism (PE). In patients with contraindications for CT pulmonary angiography (CTPA) or non-diagnostic CTPA, perfusion single-photon emission computed tomography/computed tomography (Q-SPECT/CT) is a diagnostic alternative. The goal of this study is to develop a radiomic diagnostic system to detect PE based only on the analysis of Q-SPECT/CT scans.
Methods: This radiomic diagnostic system is based on a local analysis of Q-SPECT/CT volumes that includes both CT and Q-SPECT values for each volume point. We present a combined approach that uses radiomic features extracted from each scan as input into a fully connected classifcation neural network that optimizes a weighted crossentropy loss trained to discriminate between three diferent types of image patterns (pixel sample level): healthy lungs (control group), PE and pneumonia. Four types of models using diferent confguration of parameters were tested.
Results: The proposed radiomic diagnostic system was trained on 20 patients (4,927 sets of samples of three types of image patterns) and validated in a group of 39 patients (4,410 sets of samples of three types of image patterns). In the training group, COVID-19 infection corresponded to 45% of the cases and 51.28% in the test group. In the test group, the best model for determining diferent types of image patterns with PE presented a sensitivity, specifcity, positive predictive value and negative predictive value of 75.1%, 98.2%, 88.9% and 95.4%, respectively. The best model for detecting
pneumonia presented a sensitivity, specifcity, positive predictive value and negative predictive value of 94.1%, 93.6%, 85.2% and 97.6%, respectively. The area under the curve (AUC) was 0.92 for PE and 0.91 for pneumonia. When the results obtained at the pixel sample level are aggregated into regions of interest, the sensitivity of the PE increases to 85%, and all metrics improve for pneumonia.
Conclusion: This radiomic diagnostic system was able to identify the diferent lung imaging patterns and is a frst step toward a comprehensive intelligent radiomic system to optimize the diagnosis of PE by Q-SPECT/CT. |
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5 dec 2022 |
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no |
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Admin @ si @ BGG2022 |
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3759 |
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Author |
Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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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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2023 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCARS |
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Admin @ si @ TGM2023 |
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3830 |
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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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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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IAM |
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no |
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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 |
![goto web page url](http://refbase.cvc.uab.es/img/www.gif)
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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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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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IAM |
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no |
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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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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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IAM |
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no |
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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 |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
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Title |
Detection of Epileptic Seizures Based-on Channel Fusion and Transformer Network in EEG Recordings |
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2023 |
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International Journal of Advanced Computer Science and Applications |
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IJACSA |
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14 |
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5 |
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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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IAM |
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no |
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Admin @ si @ |
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3856 |
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Author |
Josep Llados; Enric Marti; Juan J.Villanueva |
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Title |
Symbol recognition by error-tolerant subgraph matching between region adjacency graphs |
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2001 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence |
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23 |
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10 |
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1137-1143 |
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The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
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Notes ![sorted by Notes field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
DAG;IAM;ISE; |
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no |
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IAM @ iam @ LMV2001 |
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1581 |
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Author |
Josep Llados; Horst Bunke; Enric Marti |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
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Title |
Finding rotational symmetries by cyclic string matching |
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Journal Article |
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1997 |
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Pattern recognition letters |
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PRL |
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18 |
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14 |
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1435-1442 |
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Rotational symmetry; Reflectional symmetry; String matching |
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Symmetry is an important shape feature. In this paper, a simple and fast method to detect perfect and distorted rotational symmetries of 2D objects is described. The boundary of a shape is polygonally approximated and represented as a string. Rotational symmetries are found by cyclic string matching between two identical copies of the shape string. The set of minimum cost edit sequences that transform the shape string to a cyclically shifted version of itself define the rotational symmetry and its order. Finally, a modification of the algorithm is proposed to detect reflectional symmetries. Some experimental results are presented to show the reliability of the proposed algorithm |
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Elsevier |
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DAG;IAM; |
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IAM @ iam @ LBM1997a |
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1562 |
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Author |
Josep Llados; Enric Marti |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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Title |
A graph-edit algorithm for hand-drawn graphical document recognition and their automatic introduction into CAD systems |
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1999 |
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Machine Graphics & Vision |
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8 |
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195-211 |
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DAG;IAM; |
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IAM @ iam @ LIM1999 |
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1568 |
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Ernest Valveny; Enric Marti |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
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Title |
Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition |
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2000 |
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Graphics Recognition Recent Advances |
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1941 |
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193-208 |
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We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols. |
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Springer Verlag |
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Springer Verlag |
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