|
Records |
Links |
|
Author |
Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; M. Gomez; Antonio Tovar; L. Cano; C. Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
Ecografia Intracoronaria: Segmentacio Automatica de area de la llum |
Type |
Journal |
|
Year |
2002 |
Publication |
Revista Societat Catalana de Cardiologia |
Abbreviated Journal |
|
|
|
Volume |
4 |
Issue |
4 |
Pages |
42 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Barcelona |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
XIVe Congres de la Societat Catalana de Cardiologia |
|
|
Notes |
MILAB;IAM |
Approved |
no |
|
|
Call Number ![sorted by Call Number field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
BCNPCL @ bcnpcl @ RMF2002 |
Serial |
435 |
|
Permanent link to this record |
|
|
|
|
Author |
Debora Gil; Petia Radeva |
![download PDF file pdf](http://refbase.cvc.uab.es/img/file_PDF.gif)
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
A Regularized Curvature Flow Designed for a Selective Shape Restoration |
Type |
Journal Article |
|
Year |
2004 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
|
|
|
Volume |
13 |
Issue |
|
Pages |
1444–1458 |
|
|
Keywords |
Geometric flows, nonlinear filtering, shape recovery. |
|
|
Abstract |
Among all filtering techniques, those based exclu- sively on image level sets (geometric flows) have proven to be the less sensitive to the nature of noise and the most contrast preserving. A common feature to existent curvature flows is that they penalize high curvature, regardless of the curve regularity. This constitutes a major drawback since curvature extreme values are standard descriptors of the contour geometry. We argue that an operator designed with shape recovery purposes should include a term penalizing irregularity in the curvature rather than its magnitude. To this purpose, we present a novel geometric flow that includes a function that measures the degree of local irregularity present in the curve. A main advantage is that it achieves non-trivial steady states representing a smooth model of level curves in a noisy image. Performance of our approach is compared to classical filtering techniques in terms of quality in the restored image/shape and asymptotic behavior. We empirically prove that our approach is the technique that achieves the best compromise between image quality and evolution stabilization. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM;MILAB |
Approved |
no |
|
|
Call Number ![sorted by Call Number field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
BCNPCL @ bcnpcl @ GiR2004b |
Serial |
491 |
|
Permanent link to this record |
|
|
|
|
Author |
Guillermo Torres; Debora Gil |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
|
|
Title |
A multi-shape loss function with adaptive class balancing for the segmentation of lung structures |
Type |
Journal Article |
|
Year |
2020 |
Publication |
International Journal of Computer Assisted Radiology and Surgery |
Abbreviated Journal |
IJCAR |
|
|
Volume |
15 |
Issue |
1 |
Pages |
S154-55 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM |
Approved |
no |
|
|
Call Number ![sorted by Call Number field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Admin @ si @ ToG2020 |
Serial |
3590 |
|
Permanent link to this record |
|
|
|
|
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)
|
|
Title |
Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules – Intermediate Results of the RadioLung Project |
Type |
Journal Article |
|
Year |
2023 |
Publication |
International Journal of Computer Assisted Radiology and Surgery |
Abbreviated Journal |
IJCARS |
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM |
Approved |
no |
|
|
Call Number ![sorted by Call Number field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Admin @ si @ TGM2023 |
Serial |
3830 |
|
Permanent link to this record |
|
|
|
|
Author |
Guillermo Torres; Sonia Baeza; Carles Sanchez; Ignasi Guasch; Antoni Rosell; Debora Gil |
![goto web page (via DOI) doi](http://refbase.cvc.uab.es/img/doi.gif)
|
|
Title |
An Intelligent Radiomic Approach for Lung Cancer Screening |
Type |
Journal Article |
|
Year |
2022 |
Publication |
Applied Sciences |
Abbreviated Journal |
APPLSCI |
|
|
Volume |
12 |
Issue |
3 |
Pages |
1568 |
|
|
Keywords |
Lung cancer; Early diagnosis; Screening; Neural networks; Image embedding; Architecture optimization |
|
|
Abstract |
The efficiency of lung cancer screening for reducing mortality is hindered by the high rate of false positives. Artificial intelligence applied to radiomics could help to early discard benign cases from the analysis of CT scans. The available amount of data and the fact that benign cases are a minority, constitutes a main challenge for the successful use of state of the art methods (like deep learning), which can be biased, over-fitted and lack of clinical reproducibility. We present an hybrid approach combining the potential of radiomic features to characterize nodules in CT scans and the generalization of the feed forward networks. In order to obtain maximal reproducibility with minimal training data, we propose an embedding of nodules based on the statistical significance of radiomic features for malignancy detection. This representation space of lesions is the input to a feed
forward network, which architecture and hyperparameters are optimized using own-defined metrics of the diagnostic power of the whole system. Results of the best model on an independent set of patients achieve 100% of sensitivity and 83% of specificity (AUC = 0.94) for malignancy detection. |
|
|
Address |
Jan 2022 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
IAM; 600.139; 600.145 |
Approved |
no |
|
|
Call Number ![sorted by Call Number field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Admin @ si @ TBS2022 |
Serial |
3699 |
|
Permanent link to this record |