{"id":58556,"date":"2021-11-15T12:03:29","date_gmt":"2021-11-15T11:03:29","guid":{"rendered":"https:\/\/ircad.fr\/?page_id=58556"},"modified":"2021-11-15T12:03:29","modified_gmt":"2021-11-15T11:03:29","slug":"liver-segmentation-3d-ircadb-01","status":"publish","type":"page","link":"https:\/\/www.ircad.fr\/fr\/research-and-development\/data-sets\/liver-segmentation-3d-ircadb-01\/","title":{"rendered":"Liver segmentation \u2013 3D-ircadb-01"},"content":{"rendered":"

Liver segmentation 3D-IRCADb-01<\/h1>\n

\t\t\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\n

The\u00a03D-IRCADb-01<\/b>\u00a0database is composed of the 3D CT-scans of 10 women and 10 men with hepatic tumours in 75% of cases. The 20 folders correspond to 20 different patients, which can be downloaded individually or conjointly. The table below provides information on the image, such as liver size (width, depth, height) or the location of tumours according to Couninaud\u2019s segmentation. It also indicates the major difficulties liver segmentation software may encounter due to the contact with neighbouring organs, an atypical shape or density of the liver, or even artefacts in the image.<\/p>\n

These folders are called \u201c3D-IRCADb-1-number<\/i><\/b>\u201d (the\u00a0number<\/i>\u00a0varying between 01 and 20).. These folders are called \u201c3D-IRCADb-01-number<\/i><\/b>\u201d (the\u00a0number<\/i>\u00a0varying between 01 and 20). Each \u201c3D-IRCADb-01-number<\/i><\/b>\u201d folder contains 4 sub-folders called \u201cPATIENT_DICOM<\/b>\u201d, \u201cLABELLED_DICOM<\/b>\u201d, \u201cMASKS_DICOM<\/b>\u201d and \u201cMESHES_VTK<\/b>\u201d. These folders respectively contain the anonymized patient image in DICOM format, the labelled image corresponding to the various zones of interest segmented in DICOM format, a new set of sub-folders corresponding to the names of the various segmented zones of interest containing the DICOM image of each mask, and finally, all the files corresponding to surface meshes of the various zones of interest in VTK format.<\/p>\n

\"Creative<\/a>
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License<\/a>.<\/p>\n

For reference, please cite our publication below. For any further information, please contact us<\/a>.<\/p>\n

Soler, L., A. Hostettler, V. Agnus, A. Charnoz, J. Fasquel, J. Moreau, A. Osswald, M. Bouhadjar, and J. Marescaux. \u00ab\u00a03D image reconstruction for comparison of algorithm database: A patient specific anatomical and medical image database.<\/strong>\u00a0\u00bb IRCAD, Strasbourg, France, Tech. Rep<\/i> (2010)<\/em><\/p>\n

\t\t\t
\n\t\t\t\t\t\tDownload dataset (806Mb)
\n\t\t\t\t\t<\/a><\/p>\n

Description of the 20 cases of 3D-IRCADb-01:<\/b><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Aper\u00e7u<\/th>\nN\u00b0<\/th>\nSex<\/th>\nYear of birth<\/th>\nVoxel size
\n(mm)<\/th>\n		Image size
\n(pixels)<\/th>\n		Liver size
\n(cm)<\/th>\n		Liver
\nAverage
\ndensity<\/th>\n		Liver
\nPathologies<\/th>\n		Segmentation drawbacks<\/th>\nDownload<\/th>\n<\/tr>\n
\"\"<\/td>\n1<\/td>\nF<\/td>\n1944<\/td>\n0,57
\n0,57
\n1,6<\/td>\n		512
\n512
\n129<\/td>\n		18,3
\n15,1
\n14.1<\/td>\n		111<\/td>\n7 tumours in III, IV\/V, VII, VIII<\/td>\nstomach, pancreas, duodenum<\/td>\nDownload (37Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n2<\/td>\nF<\/td>\n1987<\/td>\n0,78
\n0,78
\n1,6<\/td>\n		512
\n512
\n172<\/td>\n		20,1
\n16,9
\n15,7<\/td>\n		84<\/td>\n1 tumour in V<\/td>\npancreas, duodenum<\/td>\nDownload (41Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n3<\/td>\nM<\/td>\n1956<\/td>\n0,62
\n0,62
\n1,25<\/td>\n		512
\n512
\n200<\/td>\n		16,7
\n14,9
\n15,2<\/td>\n		108<\/td>\n1 tumour in IV<\/td>\nArtefac due to metal<\/td>\nDownload (61Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n4<\/td>\nM<\/td>\n1942<\/td>\n0,74
\n0,74
\n2<\/td>\n		512
\n512
\n91<\/td>\n		16,9
\n12,0
\n17,2<\/td>\n		107<\/td>\n7 tumours<\/td>\nheart<\/td>\nDownload (28Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n5<\/td>\nM<\/td>\n1957<\/td>\n0,78
\n0,78
\n1,6<\/td>\n		512
\n512
\n139<\/td>\n		19,8
\n18,6
\n19,1<\/td>\n		69<\/td>\n0 tumour in Liver<\/td>\ndiaphragm, duodenum<\/td>\nDownload (42Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n6<\/td>\nM<\/td>\n1929<\/td>\n0,78
\n0,78
\n1,6<\/td>\n		512
\n512
\n135<\/td>\n		18,8
\n14,3
\n20,2<\/td>\n		105<\/td>\n20 tumours in liver<\/td>\nHeart<\/td>\nDownload (40Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n7<\/td>\nM<\/td>\n1946<\/td>\n0,78
\n0,78
\n1,6<\/td>\n		512
\n512
\n151<\/td>\n		24,9
\n15,2
\n16,6<\/td>\n		115<\/td>\n0 tumour in Liver (1 adrenal)<\/td>\nspleen<\/td>\nDownload (37Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n8<\/td>\nF<\/td>\n1970<\/td>\n0,56
\n0,56
\n1,6<\/td>\n		512
\n512
\n124<\/td>\n		23,5
\n17,1
\n12,5<\/td>\n		159<\/td>\n3 tumours in I, II and IV<\/td>\n<\/td>\nDownload (34Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n9<\/td>\nM<\/td>\n1949<\/td>\n0,87
\n0,87
\n2<\/td>\n		512
\n512
\n111<\/td>\n		20,6
\n17,0
\n18,1<\/td>\n		90<\/td>\n1 tumour in V\/VIII<\/td>\nstomach, colon<\/td>\nDownload (33Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n10<\/td>\nF<\/td>\n1953<\/td>\n0,73
\n0,73
\n1,6<\/td>\n		512
\n512
\n122<\/td>\n		18,4
\n15,5
\n14,8<\/td>\n		104<\/td>\n8 tumours<\/td>\nduodenum, pancreas<\/td>\nDownload (34Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n11<\/td>\nM<\/td>\n1966<\/td>\n0,72
\n0,72
\n1,6<\/td>\n		512
\n512
\n132<\/td>\n		19,1
\n14,4
\n16,2<\/td>\n		108<\/td>\n0 tumour in Liver<\/td>\nstomach, pancreas<\/td>\nDownload (36Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n12<\/td>\nF<\/td>\n1973<\/td>\n0,68
\n0,68
\n1,0<\/td>\n		512
\n512
\n260<\/td>\n		19,3
\n17,7
\n11,0<\/td>\n		118<\/td>\n1 tumour in VI<\/td>\n<\/td>\nDownload (65Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n13<\/td>\nM<\/td>\n1951<\/td>\n0,67
\n0,67
\n1,6<\/td>\n		512
\n512
\n122<\/td>\n		20,0
\n12,9
\n18,1<\/td>\n		111<\/td>\n20 tumours<\/td>\nduodenum, heart<\/td>\nDownload (33Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n14<\/td>\nF<\/td>\n1970<\/td>\n0,72
\n0,72
\n1,6<\/td>\n		512
\n512
\n113<\/td>\n		22,4
\n15,4
\n13,4<\/td>\n		109<\/td>\n0 tumour in Liver<\/td>\nspleen, pancreas<\/td>\nDownload (30Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n15<\/td>\nF<\/td>\n1946<\/td>\n0,78
\n0,78
\n1,6<\/td>\n		512
\n512
\n125<\/td>\n		18,8
\n17,7
\n14,7<\/td>\n		104<\/td>\n2 tumours in II and VIII<\/td>\npancreas<\/td>\nDownload (30Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n16<\/td>\nM<\/td>\n1950<\/td>\n0,70
\n0,70
\n1,6<\/td>\n		512
\n512
\n155<\/td>\n		20,2
\n17,7
\n20,2<\/td>\n		40<\/td>\n1 tumour in V<\/td>\nmuscle<\/td>\nDownload (41Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n17<\/td>\nM<\/td>\n1942<\/td>\n0,74
\n0,74
\n1,6<\/td>\n		512
\n512
\n119<\/td>\n		19,8
\n17,4
\n18,9<\/td>\n		99<\/td>\n2 tumours in II and VIII<\/td>\nstomach, heart<\/td>\nDownload (31Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n18<\/td>\nF<\/td>\n1958<\/td>\n0,74
\n0,74
\n2,5<\/td>\n		512
\n512
\n74<\/td>\n		22,5
\n15,1
\n18,6<\/td>\n		49<\/td>\n1 tumour in IV\/V<\/td>\noesophagus, muscles<\/td>\nDownload (22Mb)<\/a><\/td>\n
\"\"<\/td>\n19<\/td>\nF<\/td>\n1970<\/td>\n0,70
\n0,70
\n4<\/td>\n		512
\n512
\n124<\/td>\n		19,5
\n16,5
\n14,2<\/td>\n		135<\/td>\n46 tumours<\/td>\nstomach, duodenum, pancreas<\/td>\nDownload (31Mb)<\/a><\/td>\n<\/tr>\n
\"\"<\/td>\n20<\/td>\nF<\/td>\n1949<\/td>\n0,81
\n0,81
\n2<\/td>\n		512
\n512
\n225<\/td>\n		20,0
\n16,6
\n16,8<\/td>\n		59<\/td>\n0 tumour in Liver<\/td>\nstomach<\/td>\nDownload (63Mb)<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Liver segmentation 3D-IRCADb-01 The\u00a03D-IRCADb-01\u00a0database is composed of the 3D CT-scans of 10 women and 10 men with hepatic tumours in 75% of cases. The 20 folders correspond to 20 different patients, which can be downloaded individually or conjointly. The table below provides information on the image, such as liver size (width, depth, height) or the […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":9182,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-dataset-liver.php","meta":{"_acf_changed":false,"_faq_forminator_form_id":0,"_glp_forminator_form_id":0,"_fellowship_forminator_form_id":0,"_srs2026_forminator_form_id":0,"footnotes":""},"class_list":["post-58556","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nLiver segmentation \u2013 3D-ircadb-01 - IRCAD<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ircad.fr\/research-and-development\/data-sets\/liver-segmentation-3d-ircadb-01\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Liver segmentation \u2013 3D-ircadb-01 - IRCAD\" \/>\n<meta property=\"og:description\" content=\"Liver segmentation 3D-IRCADb-01 The\u00a03D-IRCADb-01\u00a0database is composed of the 3D CT-scans of 10 women and 10 men with hepatic tumours in 75% of cases. The 20 folders correspond to 20 different patients, which can be downloaded individually or conjointly. 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