<> <http://www.w3.org/2000/01/rdf-schema#comment> "The repository administrator has not yet configured an RDF license."^^<http://www.w3.org/2001/XMLSchema#string> .
<> <http://xmlns.com/foaf/0.1/primaryTopic> <https://discovery.ucl.ac.uk/id/eprint/10124649> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/ontology/bibo/Article> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/title> "Synthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/abstract> "Traditional quantitative MRI (qMRI) signal model fitting to diffusion-weighted MRI (DW-MRI) is slow and requires long computational time per patient. Recently, q-space learning utilises machine learning methods to overcome these issues and to infer diffusion metrics. However, most of q-space learning studies use simple multi layer perceptron (MLP) for model fitting, which might be sub-optimal when estimating more complex diffusion models with many free parameters. Previous works only investigate the application of q-space learning on diffusion models in the brain. In this work, we explore q-space learning for prostate cancer characterization. Our results show that while simple MLP is adequate to estimate parametric maps on simple models like classic VERDICT, deep residual regression networks are needed for more complex models such as VERDICT with compensated relaxation (R-VERDICT)."^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/date> "2021-05-25" .
<https://discovery.ucl.ac.uk/id/document/1288164> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/ontology/bibo/Document> .
<https://discovery.ucl.ac.uk/id/org/ext-af0a9a5baed87c407844a3f5db44597c> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Organization> .
<https://discovery.ucl.ac.uk/id/org/ext-af0a9a5baed87c407844a3f5db44597c> <http://xmlns.com/foaf/0.1/name> "IEEE"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/publisher> <https://discovery.ucl.ac.uk/id/org/ext-af0a9a5baed87c407844a3f5db44597c> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/status> <http://purl.org/ontology/bibo/status/published> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/creator> <https://discovery.ucl.ac.uk/id/person/ext-8539ff84101e9f5259499e5cba1b5c4d> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/authorList> <https://discovery.ucl.ac.uk/id/eprint/10124649#authors> .
<https://discovery.ucl.ac.uk/id/eprint/10124649#authors> <http://www.w3.org/1999/02/22-rdf-syntax-ns#_1> <https://discovery.ucl.ac.uk/id/person/ext-8539ff84101e9f5259499e5cba1b5c4d> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/creator> <https://discovery.ucl.ac.uk/id/person/ext-5f5e0619c29120a4c88affeb4bfbda5e> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/authorList> <https://discovery.ucl.ac.uk/id/eprint/10124649#authors> .
<https://discovery.ucl.ac.uk/id/eprint/10124649#authors> <http://www.w3.org/1999/02/22-rdf-syntax-ns#_2> <https://discovery.ucl.ac.uk/id/person/ext-5f5e0619c29120a4c88affeb4bfbda5e> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/creator> <https://discovery.ucl.ac.uk/id/person/ext-275f289777d1e87655de8290354abcfe> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/authorList> <https://discovery.ucl.ac.uk/id/eprint/10124649#authors> .
<https://discovery.ucl.ac.uk/id/eprint/10124649#authors> <http://www.w3.org/1999/02/22-rdf-syntax-ns#_3> <https://discovery.ucl.ac.uk/id/person/ext-275f289777d1e87655de8290354abcfe> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/creator> <https://discovery.ucl.ac.uk/id/person/ext-e14bb7d2c60083e11644480004076d61> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/authorList> <https://discovery.ucl.ac.uk/id/eprint/10124649#authors> .
<https://discovery.ucl.ac.uk/id/eprint/10124649#authors> <http://www.w3.org/1999/02/22-rdf-syntax-ns#_4> <https://discovery.ucl.ac.uk/id/person/ext-e14bb7d2c60083e11644480004076d61> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/creator> <https://discovery.ucl.ac.uk/id/person/ext-8adceab2416510273a989687fbde0008> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/authorList> <https://discovery.ucl.ac.uk/id/eprint/10124649#authors> .
<https://discovery.ucl.ac.uk/id/eprint/10124649#authors> <http://www.w3.org/1999/02/22-rdf-syntax-ns#_5> <https://discovery.ucl.ac.uk/id/person/ext-8adceab2416510273a989687fbde0008> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/creator> <https://discovery.ucl.ac.uk/id/person/ext-1c75669a4c3db1c0abc9e96ac2f4c2ed> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/authorList> <https://discovery.ucl.ac.uk/id/eprint/10124649#authors> .
<https://discovery.ucl.ac.uk/id/eprint/10124649#authors> <http://www.w3.org/1999/02/22-rdf-syntax-ns#_6> <https://discovery.ucl.ac.uk/id/person/ext-1c75669a4c3db1c0abc9e96ac2f4c2ed> .
<https://discovery.ucl.ac.uk/id/person/ext-1c75669a4c3db1c0abc9e96ac2f4c2ed> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> .
<https://discovery.ucl.ac.uk/id/person/ext-1c75669a4c3db1c0abc9e96ac2f4c2ed> <http://xmlns.com/foaf/0.1/givenName> "E"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-1c75669a4c3db1c0abc9e96ac2f4c2ed> <http://xmlns.com/foaf/0.1/familyName> "Panagiotaki"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-1c75669a4c3db1c0abc9e96ac2f4c2ed> <http://xmlns.com/foaf/0.1/name> "E Panagiotaki"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-5f5e0619c29120a4c88affeb4bfbda5e> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> .
<https://discovery.ucl.ac.uk/id/person/ext-5f5e0619c29120a4c88affeb4bfbda5e> <http://xmlns.com/foaf/0.1/givenName> "E"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-5f5e0619c29120a4c88affeb4bfbda5e> <http://xmlns.com/foaf/0.1/familyName> "Chiou"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-5f5e0619c29120a4c88affeb4bfbda5e> <http://xmlns.com/foaf/0.1/name> "E Chiou"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-e14bb7d2c60083e11644480004076d61> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> .
<https://discovery.ucl.ac.uk/id/person/ext-e14bb7d2c60083e11644480004076d61> <http://xmlns.com/foaf/0.1/givenName> "S"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-e14bb7d2c60083e11644480004076d61> <http://xmlns.com/foaf/0.1/familyName> "Singh"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-e14bb7d2c60083e11644480004076d61> <http://xmlns.com/foaf/0.1/name> "S Singh"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-8adceab2416510273a989687fbde0008> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> .
<https://discovery.ucl.ac.uk/id/person/ext-8adceab2416510273a989687fbde0008> <http://xmlns.com/foaf/0.1/givenName> "S"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-8adceab2416510273a989687fbde0008> <http://xmlns.com/foaf/0.1/familyName> "Punwani"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-8adceab2416510273a989687fbde0008> <http://xmlns.com/foaf/0.1/name> "S Punwani"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-8539ff84101e9f5259499e5cba1b5c4d> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> .
<https://discovery.ucl.ac.uk/id/person/ext-8539ff84101e9f5259499e5cba1b5c4d> <http://xmlns.com/foaf/0.1/givenName> "V"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-8539ff84101e9f5259499e5cba1b5c4d> <http://xmlns.com/foaf/0.1/familyName> "Valindria"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-8539ff84101e9f5259499e5cba1b5c4d> <http://xmlns.com/foaf/0.1/name> "V Valindria"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-275f289777d1e87655de8290354abcfe> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> .
<https://discovery.ucl.ac.uk/id/person/ext-275f289777d1e87655de8290354abcfe> <http://xmlns.com/foaf/0.1/givenName> "M"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-275f289777d1e87655de8290354abcfe> <http://xmlns.com/foaf/0.1/familyName> "Palombo"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/person/ext-275f289777d1e87655de8290354abcfe> <http://xmlns.com/foaf/0.1/name> "M Palombo"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/ontology/bibo/Article> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/ontology/bibo/presentedAt> <https://discovery.ucl.ac.uk/id/event/ext-6f108967ade6e99cff087d6bb01e7358> .
<https://discovery.ucl.ac.uk/id/event/ext-6f108967ade6e99cff087d6bb01e7358> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/ontology/bibo/Conference> .
<https://discovery.ucl.ac.uk/id/event/ext-6f108967ade6e99cff087d6bb01e7358> <http://purl.org/dc/terms/title> "IEEE International Symposium on Biomedical Imaging (ISBI), Nice, France, 13-16 April 2021"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/EPrint> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/ProceedingsSectionEPrint> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/terms/isPartOf> <https://discovery.ucl.ac.uk/id/repository> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://eprints.org/ontology/hasDocument> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288164> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/Document> .
<https://discovery.ucl.ac.uk/id/document/1288164> <http://www.w3.org/2000/01/rdf-schema#label> "Synthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT (Text)"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://purl.org/dc/elements/1.1/hasVersion> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://eprints.org/ontology/hasPublished> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288164> <http://eprints.org/ontology/hasFile> <https://discovery.ucl.ac.uk/id/eprint/10124649/1/ISBI_2021_Valindria_Final.pdf> .
<https://discovery.ucl.ac.uk/id/document/1288164> <http://purl.org/dc/terms/hasPart> <https://discovery.ucl.ac.uk/id/eprint/10124649/1/ISBI_2021_Valindria_Final.pdf> .
<https://discovery.ucl.ac.uk/id/eprint/10124649/1/ISBI_2021_Valindria_Final.pdf> <http://www.w3.org/2000/01/rdf-schema#label> "ISBI_2021_Valindria_Final.pdf"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://eprints.org/ontology/hasDocument> <https://discovery.ucl.ac.uk/id/document/1288165> .
<https://discovery.ucl.ac.uk/id/document/1288165> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/Document> .
<https://discovery.ucl.ac.uk/id/document/1288165> <http://www.w3.org/2000/01/rdf-schema#label> "Synthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT (Other)"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/document/1288165> <http://eprints.org/relation/isVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288165> <http://eprints.org/relation/isVolatileVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288165> <http://eprints.org/relation/islightboxThumbnailVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288165> <http://eprints.org/ontology/hasFile> <https://discovery.ucl.ac.uk/id/eprint/10124649/2/lightbox.jpg> .
<https://discovery.ucl.ac.uk/id/document/1288165> <http://purl.org/dc/terms/hasPart> <https://discovery.ucl.ac.uk/id/eprint/10124649/2/lightbox.jpg> .
<https://discovery.ucl.ac.uk/id/eprint/10124649/2/lightbox.jpg> <http://www.w3.org/2000/01/rdf-schema#label> "lightbox.jpg"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://eprints.org/ontology/hasDocument> <https://discovery.ucl.ac.uk/id/document/1288166> .
<https://discovery.ucl.ac.uk/id/document/1288166> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/Document> .
<https://discovery.ucl.ac.uk/id/document/1288166> <http://www.w3.org/2000/01/rdf-schema#label> "Synthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT (Other)"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/document/1288166> <http://eprints.org/relation/isVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288166> <http://eprints.org/relation/isVolatileVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288166> <http://eprints.org/relation/ispreviewThumbnailVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288166> <http://eprints.org/ontology/hasFile> <https://discovery.ucl.ac.uk/id/eprint/10124649/3/preview.jpg> .
<https://discovery.ucl.ac.uk/id/document/1288166> <http://purl.org/dc/terms/hasPart> <https://discovery.ucl.ac.uk/id/eprint/10124649/3/preview.jpg> .
<https://discovery.ucl.ac.uk/id/eprint/10124649/3/preview.jpg> <http://www.w3.org/2000/01/rdf-schema#label> "preview.jpg"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://eprints.org/ontology/hasDocument> <https://discovery.ucl.ac.uk/id/document/1288167> .
<https://discovery.ucl.ac.uk/id/document/1288167> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/Document> .
<https://discovery.ucl.ac.uk/id/document/1288167> <http://www.w3.org/2000/01/rdf-schema#label> "Synthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT (Other)"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/document/1288167> <http://eprints.org/relation/isVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288167> <http://eprints.org/relation/isVolatileVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288167> <http://eprints.org/relation/ismediumThumbnailVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288167> <http://eprints.org/ontology/hasFile> <https://discovery.ucl.ac.uk/id/eprint/10124649/4/medium.jpg> .
<https://discovery.ucl.ac.uk/id/document/1288167> <http://purl.org/dc/terms/hasPart> <https://discovery.ucl.ac.uk/id/eprint/10124649/4/medium.jpg> .
<https://discovery.ucl.ac.uk/id/eprint/10124649/4/medium.jpg> <http://www.w3.org/2000/01/rdf-schema#label> "medium.jpg"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://eprints.org/ontology/hasDocument> <https://discovery.ucl.ac.uk/id/document/1288168> .
<https://discovery.ucl.ac.uk/id/document/1288168> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/Document> .
<https://discovery.ucl.ac.uk/id/document/1288168> <http://www.w3.org/2000/01/rdf-schema#label> "Synthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT (Other)"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/document/1288168> <http://eprints.org/relation/isVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288168> <http://eprints.org/relation/isVolatileVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288168> <http://eprints.org/relation/issmallThumbnailVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288168> <http://eprints.org/ontology/hasFile> <https://discovery.ucl.ac.uk/id/eprint/10124649/5/small.jpg> .
<https://discovery.ucl.ac.uk/id/document/1288168> <http://purl.org/dc/terms/hasPart> <https://discovery.ucl.ac.uk/id/eprint/10124649/5/small.jpg> .
<https://discovery.ucl.ac.uk/id/eprint/10124649/5/small.jpg> <http://www.w3.org/2000/01/rdf-schema#label> "small.jpg"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://eprints.org/ontology/hasDocument> <https://discovery.ucl.ac.uk/id/document/1288169> .
<https://discovery.ucl.ac.uk/id/document/1288169> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://eprints.org/ontology/Document> .
<https://discovery.ucl.ac.uk/id/document/1288169> <http://www.w3.org/2000/01/rdf-schema#label> "Synthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT (Other)"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/document/1288169> <http://eprints.org/relation/isVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288169> <http://eprints.org/relation/isVolatileVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288169> <http://eprints.org/relation/isIndexCodesVersionOf> <https://discovery.ucl.ac.uk/id/document/1288164> .
<https://discovery.ucl.ac.uk/id/document/1288169> <http://eprints.org/ontology/hasFile> <https://discovery.ucl.ac.uk/id/eprint/10124649/6/indexcodes.txt> .
<https://discovery.ucl.ac.uk/id/document/1288169> <http://purl.org/dc/terms/hasPart> <https://discovery.ucl.ac.uk/id/eprint/10124649/6/indexcodes.txt> .
<https://discovery.ucl.ac.uk/id/eprint/10124649/6/indexcodes.txt> <http://www.w3.org/2000/01/rdf-schema#label> "indexcodes.txt"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10124649> <http://www.w3.org/2000/01/rdf-schema#seeAlso> <https://discovery.ucl.ac.uk/id/eprint/10124649/> .
<https://discovery.ucl.ac.uk/id/eprint/10124649/> <http://purl.org/dc/elements/1.1/title> "HTML Summary of #10124649 \n\nSynthetic Q-Space Learning with Deep Regression Networks for Prostate Cancer Characterisation with VERDICT\n\n" .
<https://discovery.ucl.ac.uk/id/eprint/10124649/> <http://purl.org/dc/elements/1.1/format> "text/html" .
<https://discovery.ucl.ac.uk/id/eprint/10124649/> <http://xmlns.com/foaf/0.1/primaryTopic> <https://discovery.ucl.ac.uk/id/eprint/10124649> .