Comparisons of outcome and prognostic features among histologic subtypes of renal cell carcinoma. The American journal of surgical pathology, pp.612-624, 2003. ,
Vessel segmentation in angiograms using hysteresis thresholding, IAPR Conference on Machine Vision Applications . Citeseer, 2005. ,
Multiscale vessel enhancement filtering, Medical Image Computing and Computer-Assisted InterventationMIC- CAI98, pp.130-137, 1998. ,
Prognostic significance of morphologic parameters in renal cell carcinoma, The American journal of surgical pathology, vol.6, issue.7, pp.655-664, 1982. ,
PicToSeek: combining color and shape invariant features for image retrieval, IEEE Transactions on Image Processing, vol.9, issue.1, pp.102-119, 2000. ,
DOI : 10.1109/83.817602
Gene expression patterns in renal cell carcinoma assessed by complementary dna microarray, The American journal of pathology, vol.162, issue.3, pp.925-932, 2003. ,
Document binarization with automatic parameter tuning, International Journal on Document Analysis and Recognition (IJDAR), vol.16, issue.3, pp.247-258, 2013. ,
Timeefficient sparse analysis of histopathological whole slide images. Computerized medical imaging and graphics, pp.579-591, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00553877
Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review—Current Status and Future Potential, IEEE Reviews in Biomedical Engineering, vol.7, pp.97-114, 2014. ,
DOI : 10.1109/RBME.2013.2295804
Renal cell carcinoma, BMJ, vol.349, issue.nov10 11, 2014. ,
DOI : 10.1136/bmj.g4797
Histopathology of surgically treated renal cell carcinoma: survival differences by subtype and stage, The Journal of urology, vol.188, issue.2, pp.391-397, 2012. ,
Model-Based Detection of Tubular Structures in 3D Images, Computer Vision and Image Understanding, vol.80, issue.2, pp.130-171, 2000. ,
DOI : 10.1006/cviu.2000.0866
URL : https://hal.archives-ouvertes.fr/inria-00615029
Thinning methodologies-a comprehensive survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.9 ,
DOI : 10.1109/34.161346
2004 WHO Classification of the Renal Tumors of the Adults, European Urology, vol.49, issue.5, pp.798-805, 2006. ,
DOI : 10.1016/j.eururo.2005.11.035
Axon Morphology Analysis: from Image Processing to Modelling. Theses Classification of tumor histopathology via sparse feature learning, (UNS) Biomedical Imaging (ISBI), IEEE International Symposium on, pp.410-413, 2013. ,
Computer-aided identification of prostatic adenocarcinoma: Segmentation of glandular structures, Journal of Pathology Informatics, vol.2, issue.1, 2011. ,
DOI : 10.4103/2153-3539.83193
Microscopic analysis and significance of vascular architectural complexity in renal cell carcinoma, Clinical Cancer Research, vol.7, issue.3, pp.533-537, 2001. ,
Renal cell carcinoma and normal kidney protein expression, Electrophoresis, vol.13, issue.3-4, pp.3-4599, 1997. ,
DOI : 10.1002/elps.1150180343
Classification of renal cell carcinoma, Cancer, vol.80, issue.5, pp.987-989, 1997. ,
DOI : 10.1002/(SICI)1097-0142(19970901)80:5<987::AID-CNCR24>3.0.CO;2-R
Automated grading of renal cell carcinoma using whole slide imaging, Journal of pathology informatics, vol.5, 2014. ,