BUSCADOR RECOLECTA

The different algorithms of the "imbalanced-learn" toolbox are evaluated on a set of common dataset, which are more or less balanced. These benchmark have been proposed in Ding, Zejin, "Diversified Ensemble Classifiers for H ighly Imbalanced Data Learning and their Application in Bioinformatics." Dissertation, Georgia State University, (2011)

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of prostate cancer to facilitate its diagnosis. A 3mm slice fat-suppressed T2W fast spin-echo sequence (TR/TE/ETL: 3400 ms/85 ms/13) is used to acquire images in sagittal and oblique coronal planes, the latter planes being orientated perpendicular or parallel to the prostate PZ – rectal wall axis. Three-dimensional T2W fast spin-echo (TR/TE/ETL: 3600 ms}/143 ms/109, slice thickness: 1.25 mm) images are then acquired in an oblique axial plane.The nominal matrix and FoV of the 3D T2W fast spin-echo images are 320x256 and 280x240 mm2, respectively, thereby affording sub-millimetric pixel resolution within the imaging plane.\nDCE-MRI is performed using a fat suppressed 3D T$_1$ VIBE sequence (TR/TE/Flip angle: 3.25 ms/1.12 ms/10 degrees; Matrix: 256x192; FoV: 280x210 (with 75% rectangular FoV); slab of 16 partitions of 3.5 mm thickness; temporal resolution: 6 s/slab over approximately 5 min). A power injector (Medrad, Indianola, USA) is used to provide a bolus injection of Gd-DTPA (Dotarem, Guerbet, Roissy, France) at a dose of 0.2 ml Gd-DTPA/kg of body weight

Development and investigation of a multiparametric magnetic resonance CAD system for prostate cancer (CaP) detection. Data associated with chapter 6 of Guillaume Lemaitre's doctoral thesis

Multi-parametric magnetic resonance imaging (MRI) dataset for prostate cancer detection. The purpose of this dataset is to help at the development of computer-aided detection and diagnosis (CAD) system of prostate cancer (CaP)

Dades associades a l'article publicat: Lemaitre, G., Marti, R., Freixenet, J., Vilanova, J.C., Walker, P.M. i Meriaudeau, F. (2015). Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review. Computers in Biology and Medicine, vol. 60, p. 8-31. Disponible a https://doi.org/10.1016/j.compbiomed.2015.02.009, Instruccions per obrir els fitxers: cal concatenar els fitxers per crear el fitxer original. Dps es pot descomprimir amb tar al linux i amb 7zip al windows. Amb Linux console: cat file1 file2 file3 ... > file.tar.gz, descomprimir: tar -xzf file.tar.gz. I amb windows console: type file1 file2 file3 ... > file.tar.gz, descomprimir amb 7zip, Dataset available at I2CVB http://i2cvb.github.io/, Multi-parametric magnetic resonance imaging (MRI) dataset for prostate cancer detection. The purpose of this dataset is to help at the development of computer-aided detection and diagnosis (CAD) system of prostate cancer (CaP)

Instruccions per obrir els fitxers: cal concatenar els fitxers per crear el fitxer original. Dps es pot descomprimir amb tar al linux i amb 7zip al windows. Amb Linux console: cat file1 file2 file3 ... > file.tar.gz, descomprimir: tar -xzf file.tar.gz. I amb windows console: type file1 file2 file3 ... > file.tar.gz, descomprimir amb 7zip, Dades associades amb el capítol 6 de la següent tesi doctoral: Lemaître, Guillaume. “Computer-Aided Diagnosis for Prostate Cancer using Multi-Parametric Magnetic Resonance Imaging”. Tesi. Universitat de Girona i Université de Bourgogne Franche-Comté, 2016, Development and investigation of a multiparametric magnetic resonance CAD system for prostate cancer (CaP) detection. Data used for the pipeline developed in https://github.com/I2Cvb/mp-mri-prostate, Desenvolupament i investigació d'un sistema CAD de ressonància magnètica multiparamètrica per a la detecció del càncer de pròstata (CaP). Dades utilitzades per al pipeline desenvolupat a https://github.com/I2Cvb/mp-mri-prostate

Instruccions per obrir els fitxers: cal concatenar els fitxers per crear el fitxer original. Dps es pot descomprimir amb tar al linux i amb 7zip al windows. Amb Linux console: cat file1 file2 file3 ... > file.tar.gz, descomprimir: tar -xzf file.tar.gz. I amb windows console: type file1 file2 file3 ... > file.tar.gz, descomprimir amb 7zip, Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of prostate cancer to facilitate its diagnosis. A 3mm slice fat-suppressed T2W fast spin-echo sequence (TR/TE/ETL: 3400 ms/85 ms/13) is used to acquire images in sagittal and oblique coronal planes, the latter planes being orientated perpendicular or parallel to the prostate PZ – rectal wall axis. Three-dimensional T2W fast spin-echo (TR/TE/ETL: 3600 ms}/143 ms/109, slice thickness: 1.25 mm) images are then acquired in an oblique axial plane.The nominal matrix and FoV of the 3D T2W fast spin-echo images are 320x256 and 280x240 mm2, respectively, thereby affording sub-millimetric pixel resolution within the imaging plane.\nDCE-MRI is performed using a fat suppressed 3D T$_1$ VIBE sequence (TR/TE/Flip angle: 3.25 ms/1.12 ms/10 degrees; Matrix: 256x192; FoV: 280x210 (with 75% rectangular FoV); slab of 16 partitions of 3.5 mm thickness; temporal resolution: 6 s/slab over approximately 5 min). A power injector (Medrad, Indianola, USA) is used to provide a bolus injection of Gd-DTPA (Dotarem, Guerbet, Roissy, France) at a dose of 0.2 ml Gd-DTPA/kg of body weight

Instruccions per obrir els fitxers: cal concatenar els fitxers per crear el fitxer original. Dps es pot descomprimir amb tar al linux i amb 7zip al windows. Amb Linux console: cat file1 file2 file3 ... > file.tar.gz, descomprimir: tar -xzf file.tar.gz. I amb windows console: type file1 file2 file3 ... > file.tar.gz, descomprimir amb 7zip, The different algorithms of the "imbalanced-learn" toolbox are evaluated on a set of common dataset, which are more or less balanced. These benchmark have been proposed in Ding, Zejin, "Diversified Ensemble Classifiers for H ighly Imbalanced Data Learning and their Application in Bioinformatics." Dissertation, Georgia State University, (2011)