{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:W3FD2VYJ7T5BMAFWLQYNXFFW73","short_pith_number":"pith:W3FD2VYJ","schema_version":"1.0","canonical_sha256":"b6ca3d5709fcfa1600b65c30db94b6fed9497b27da650123bb32d1dc7577652d","source":{"kind":"arxiv","id":"1811.06065","version":1},"attestation_state":"computed","paper":{"title":"Spatial Logics and Model Checking for Medical Imaging (Extended Version)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LO","authors_text":"Diego Latella, Fabrizio Banci Buonamici, Gina Belmonte, Mieke Massink, Vincenzo Ciancia","submitted_at":"2018-11-14T21:02:31Z","abstract_excerpt":"Recent research on spatial and spatio-temporal model checking provides novel image analysis methodologies, rooted in logical methods for topological spaces. Medical Imaging (MI) is a field where such methods show potential for ground-breaking innovation. Our starting point is SLCS, the Spatial Logic for Closure Spaces -- Closure Spaces being a generalisation of topological spaces, covering also discrete space structures -- and topochecker, a model-checker for SLCS (and extensions thereof). We introduce the logical language ImgQL (\"Image Query Language\"). ImgQL extends SLCS with logical operato"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1811.06065","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2018-11-14T21:02:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"3005dcc3957bc3b670b13be49b6e47afd97c707c0f2ef31ea10664bfa3a47ae1","abstract_canon_sha256":"271b8856d782335b745454094b134c33cdbeead7d0ba82ad7b04fc1dacd8e64a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:38.748990Z","signature_b64":"B+BlzWwzc8u5YdVsV2RiuXhdjaLssyDUVY4DMrb7reZyE7mjt7rJxK3Ig/tW17kDmBOmcmTQl5My5O8ajDNZDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6ca3d5709fcfa1600b65c30db94b6fed9497b27da650123bb32d1dc7577652d","last_reissued_at":"2026-05-18T00:00:38.748349Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:38.748349Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Spatial Logics and Model Checking for Medical Imaging (Extended Version)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LO","authors_text":"Diego Latella, Fabrizio Banci Buonamici, Gina Belmonte, Mieke Massink, Vincenzo Ciancia","submitted_at":"2018-11-14T21:02:31Z","abstract_excerpt":"Recent research on spatial and spatio-temporal model checking provides novel image analysis methodologies, rooted in logical methods for topological spaces. Medical Imaging (MI) is a field where such methods show potential for ground-breaking innovation. Our starting point is SLCS, the Spatial Logic for Closure Spaces -- Closure Spaces being a generalisation of topological spaces, covering also discrete space structures -- and topochecker, a model-checker for SLCS (and extensions thereof). We introduce the logical language ImgQL (\"Image Query Language\"). ImgQL extends SLCS with logical operato"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.06065","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1811.06065","created_at":"2026-05-18T00:00:38.748486+00:00"},{"alias_kind":"arxiv_version","alias_value":"1811.06065v1","created_at":"2026-05-18T00:00:38.748486+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.06065","created_at":"2026-05-18T00:00:38.748486+00:00"},{"alias_kind":"pith_short_12","alias_value":"W3FD2VYJ7T5B","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_16","alias_value":"W3FD2VYJ7T5BMAFW","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_8","alias_value":"W3FD2VYJ","created_at":"2026-05-18T12:32:59.047623+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73","json":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73.json","graph_json":"https://pith.science/api/pith-number/W3FD2VYJ7T5BMAFWLQYNXFFW73/graph.json","events_json":"https://pith.science/api/pith-number/W3FD2VYJ7T5BMAFWLQYNXFFW73/events.json","paper":"https://pith.science/paper/W3FD2VYJ"},"agent_actions":{"view_html":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73","download_json":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73.json","view_paper":"https://pith.science/paper/W3FD2VYJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1811.06065&json=true","fetch_graph":"https://pith.science/api/pith-number/W3FD2VYJ7T5BMAFWLQYNXFFW73/graph.json","fetch_events":"https://pith.science/api/pith-number/W3FD2VYJ7T5BMAFWLQYNXFFW73/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73/action/storage_attestation","attest_author":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73/action/author_attestation","sign_citation":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73/action/citation_signature","submit_replication":"https://pith.science/pith/W3FD2VYJ7T5BMAFWLQYNXFFW73/action/replication_record"}},"created_at":"2026-05-18T00:00:38.748486+00:00","updated_at":"2026-05-18T00:00:38.748486+00:00"}