{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:X7IDV6MAHWBGLCU72K62YYTI6K","short_pith_number":"pith:X7IDV6MA","canonical_record":{"source":{"id":"1703.00035","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-28T19:36:34Z","cross_cats_sorted":[],"title_canon_sha256":"46f6a10b6d82528398ddbb81aaf7b491dc896db325a463bcdddea6d15075a915","abstract_canon_sha256":"bb97494543b0161b170c34bf724d428a2c5d343dc07f9fe1b8f4acc32bb8283d"},"schema_version":"1.0"},"canonical_sha256":"bfd03af9803d82658a9fd2bdac6268f2a51bc955f5c47fef7f5a5a0438dcc331","source":{"kind":"arxiv","id":"1703.00035","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.00035","created_at":"2026-05-18T00:34:31Z"},{"alias_kind":"arxiv_version","alias_value":"1703.00035v3","created_at":"2026-05-18T00:34:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.00035","created_at":"2026-05-18T00:34:31Z"},{"alias_kind":"pith_short_12","alias_value":"X7IDV6MAHWBG","created_at":"2026-05-18T12:31:53Z"},{"alias_kind":"pith_short_16","alias_value":"X7IDV6MAHWBGLCU7","created_at":"2026-05-18T12:31:53Z"},{"alias_kind":"pith_short_8","alias_value":"X7IDV6MA","created_at":"2026-05-18T12:31:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:X7IDV6MAHWBGLCU72K62YYTI6K","target":"record","payload":{"canonical_record":{"source":{"id":"1703.00035","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-28T19:36:34Z","cross_cats_sorted":[],"title_canon_sha256":"46f6a10b6d82528398ddbb81aaf7b491dc896db325a463bcdddea6d15075a915","abstract_canon_sha256":"bb97494543b0161b170c34bf724d428a2c5d343dc07f9fe1b8f4acc32bb8283d"},"schema_version":"1.0"},"canonical_sha256":"bfd03af9803d82658a9fd2bdac6268f2a51bc955f5c47fef7f5a5a0438dcc331","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:31.181331Z","signature_b64":"Nf7ca7FKEsqKoogcQDOkeHvuANBg9z9pWLXCT/na6CBN/xe4jdNMJkcABU9lZO2akd0xCnIvqzoNheaHSEn+Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bfd03af9803d82658a9fd2bdac6268f2a51bc955f5c47fef7f5a5a0438dcc331","last_reissued_at":"2026-05-18T00:34:31.180944Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:31.180944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.00035","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:34:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ziavb6eQvxHESWFvm5hIY/sfzR/hTbWQNJCGrwZDX3c6XtW0/86HDCtoNyVpEU5AG6qynb7zj7r/uulvwep6BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T04:43:26.357671Z"},"content_sha256":"fe072a0576e88fb8dc15731e5e8d319d8a176f081f11b3c48c22a420db2037ed","schema_version":"1.0","event_id":"sha256:fe072a0576e88fb8dc15731e5e8d319d8a176f081f11b3c48c22a420db2037ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:X7IDV6MAHWBGLCU72K62YYTI6K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amir Alansary, Benjamin Hou, Bernhard Kainz, Jo V. Hajnal, Konstantinos Kamnitsas, Mary Rutherford, Ozan Oktay, Steven McDonagh","submitted_at":"2017-02-28T19:36:34Z","abstract_excerpt":"3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast but low-resolution image acquisition and highly detailed but slow image acquisition. Fast imaging is required for targets that move to avoid motion artefacts. This is in particular difficult for fetal MRI. Spatially independent upsampling techniques, which are the state-of-the-art to address this problem, are error prone and disregard contextual information. In this paper we propose a context-sensitive upsampling method based on a residual convolutional neural network model that learns organ specific appearance and adopts se"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.00035","kind":"arxiv","version":3},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:34:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gl4DWRyG+dHaasPjRntVSARU/uyfIPBgK3TteWLv7KUg6SR1DVp68OLVM1L6em+aZUAkpzFdmWD4rxEgqpnJAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T04:43:26.358191Z"},"content_sha256":"af14674480aaf2ce1396572d6b56533f7cc6ab112ad8f267ee0294bb710ee878","schema_version":"1.0","event_id":"sha256:af14674480aaf2ce1396572d6b56533f7cc6ab112ad8f267ee0294bb710ee878"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X7IDV6MAHWBGLCU72K62YYTI6K/bundle.json","state_url":"https://pith.science/pith/X7IDV6MAHWBGLCU72K62YYTI6K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X7IDV6MAHWBGLCU72K62YYTI6K/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-26T04:43:26Z","links":{"resolver":"https://pith.science/pith/X7IDV6MAHWBGLCU72K62YYTI6K","bundle":"https://pith.science/pith/X7IDV6MAHWBGLCU72K62YYTI6K/bundle.json","state":"https://pith.science/pith/X7IDV6MAHWBGLCU72K62YYTI6K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X7IDV6MAHWBGLCU72K62YYTI6K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:X7IDV6MAHWBGLCU72K62YYTI6K","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"bb97494543b0161b170c34bf724d428a2c5d343dc07f9fe1b8f4acc32bb8283d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-28T19:36:34Z","title_canon_sha256":"46f6a10b6d82528398ddbb81aaf7b491dc896db325a463bcdddea6d15075a915"},"schema_version":"1.0","source":{"id":"1703.00035","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.00035","created_at":"2026-05-18T00:34:31Z"},{"alias_kind":"arxiv_version","alias_value":"1703.00035v3","created_at":"2026-05-18T00:34:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.00035","created_at":"2026-05-18T00:34:31Z"},{"alias_kind":"pith_short_12","alias_value":"X7IDV6MAHWBG","created_at":"2026-05-18T12:31:53Z"},{"alias_kind":"pith_short_16","alias_value":"X7IDV6MAHWBGLCU7","created_at":"2026-05-18T12:31:53Z"},{"alias_kind":"pith_short_8","alias_value":"X7IDV6MA","created_at":"2026-05-18T12:31:53Z"}],"graph_snapshots":[{"event_id":"sha256:af14674480aaf2ce1396572d6b56533f7cc6ab112ad8f267ee0294bb710ee878","target":"graph","created_at":"2026-05-18T00:34:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast but low-resolution image acquisition and highly detailed but slow image acquisition. Fast imaging is required for targets that move to avoid motion artefacts. This is in particular difficult for fetal MRI. Spatially independent upsampling techniques, which are the state-of-the-art to address this problem, are error prone and disregard contextual information. In this paper we propose a context-sensitive upsampling method based on a residual convolutional neural network model that learns organ specific appearance and adopts se","authors_text":"Amir Alansary, Benjamin Hou, Bernhard Kainz, Jo V. Hajnal, Konstantinos Kamnitsas, Mary Rutherford, Ozan Oktay, Steven McDonagh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-28T19:36:34Z","title":"Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.00035","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:fe072a0576e88fb8dc15731e5e8d319d8a176f081f11b3c48c22a420db2037ed","target":"record","created_at":"2026-05-18T00:34:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"bb97494543b0161b170c34bf724d428a2c5d343dc07f9fe1b8f4acc32bb8283d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-28T19:36:34Z","title_canon_sha256":"46f6a10b6d82528398ddbb81aaf7b491dc896db325a463bcdddea6d15075a915"},"schema_version":"1.0","source":{"id":"1703.00035","kind":"arxiv","version":3}},"canonical_sha256":"bfd03af9803d82658a9fd2bdac6268f2a51bc955f5c47fef7f5a5a0438dcc331","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bfd03af9803d82658a9fd2bdac6268f2a51bc955f5c47fef7f5a5a0438dcc331","first_computed_at":"2026-05-18T00:34:31.180944Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:34:31.180944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Nf7ca7FKEsqKoogcQDOkeHvuANBg9z9pWLXCT/na6CBN/xe4jdNMJkcABU9lZO2akd0xCnIvqzoNheaHSEn+Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:34:31.181331Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.00035","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fe072a0576e88fb8dc15731e5e8d319d8a176f081f11b3c48c22a420db2037ed","sha256:af14674480aaf2ce1396572d6b56533f7cc6ab112ad8f267ee0294bb710ee878"],"state_sha256":"9dbeba4ec88b753a56201a7cc0e0e9d1d0c0d7268e0fd80bd17aae9536a95dff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J8g6+OF62K9T9OOYYLcFTXZ+d8MDAr/iAb1/0AcVGtuSPA0V8vEGuGcPRhaDaHD2KiMMN66HhW/NprgopMC6Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T04:43:26.361067Z","bundle_sha256":"5cfa4e7add15946d7ec034d95b326425b8697a8cdf5bdb6e7c3e5e4d0899a144"}}