{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ZNMHH74QF3XFMCAQ3B4DNNHJG6","short_pith_number":"pith:ZNMHH74Q","canonical_record":{"source":{"id":"1803.01417","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-04T20:45:06Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"0090848f3c87fd8021372737e6236140a270d6c267f48f3d4fd6cd765734d168","abstract_canon_sha256":"066596d51cf2d7e5e84ac07d4a3cc98f7cd19143fd13d2cc8446ab98e2d43f9e"},"schema_version":"1.0"},"canonical_sha256":"cb5873ff902eee560810d87836b4e937a58cf32cadd168f0b532b581fd34efd7","source":{"kind":"arxiv","id":"1803.01417","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.01417","created_at":"2026-05-18T00:13:44Z"},{"alias_kind":"arxiv_version","alias_value":"1803.01417v3","created_at":"2026-05-18T00:13:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.01417","created_at":"2026-05-18T00:13:44Z"},{"alias_kind":"pith_short_12","alias_value":"ZNMHH74QF3XF","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZNMHH74QF3XFMCAQ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZNMHH74Q","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ZNMHH74QF3XFMCAQ3B4DNNHJG6","target":"record","payload":{"canonical_record":{"source":{"id":"1803.01417","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-04T20:45:06Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"0090848f3c87fd8021372737e6236140a270d6c267f48f3d4fd6cd765734d168","abstract_canon_sha256":"066596d51cf2d7e5e84ac07d4a3cc98f7cd19143fd13d2cc8446ab98e2d43f9e"},"schema_version":"1.0"},"canonical_sha256":"cb5873ff902eee560810d87836b4e937a58cf32cadd168f0b532b581fd34efd7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:44.688503Z","signature_b64":"nMkVxGaPNg087c+LsX+pKI9iZOsj2dhQ85TZ11egm/m0b6yMF0skhRlsRDfbWKWqC/SdvodBOQLQTbMrpKjlDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb5873ff902eee560810d87836b4e937a58cf32cadd168f0b532b581fd34efd7","last_reissued_at":"2026-05-18T00:13:44.687728Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:44.687728Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.01417","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":"2026-05-18T00:13:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w8suWP9W/mxCoqSyolpppE1aZ9lozbe0O8qU1t8FO364yRS/vEXo772sQuhFxhyr4w9K0vGQMd3dVMWg3KKpDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T14:19:58.928589Z"},"content_sha256":"cd4bd3b504f8016e140b089c31bfccff62dd6b2ca4726508a654546cf6027f03","schema_version":"1.0","event_id":"sha256:cd4bd3b504f8016e140b089c31bfccff62dd6b2ca4726508a654546cf6027f03"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ZNMHH74QF3XFMCAQ3B4DNNHJG6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Anthony G. Christodoulou, Debiao Li, Feng Shi, Yibin Xie, Yuhua Chen, ZhengWei Zhou","submitted_at":"2018-03-04T20:45:06Z","abstract_excerpt":"High-resolution (HR) magnetic resonance images (MRI) provide detailed anatomical information important for clinical application and quantitative image analysis. However, HR MRI conventionally comes at the cost of longer scan time, smaller spatial coverage, and lower signal-to-noise ratio (SNR). Recent studies have shown that single image super-resolution (SISR), a technique to recover HR details from one single low-resolution (LR) input image, could provide high-quality image details with the help of advanced deep convolutional neural networks (CNN). However, deep neural networks consume memor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.01417","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":"2026-05-18T00:13:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t0Xn8t3ir4DMIEy8S3CYhrvSBkoxAwVrPmrxt2K6TheWvZKtWqohWxaMX3FFgKhJ4xDSIdrEpLJRgFb31PACCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T14:19:58.928936Z"},"content_sha256":"6446e342b193298c69ed0658a1b78e5b057a1b1321e72049186d716a3906bdb5","schema_version":"1.0","event_id":"sha256:6446e342b193298c69ed0658a1b78e5b057a1b1321e72049186d716a3906bdb5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZNMHH74QF3XFMCAQ3B4DNNHJG6/bundle.json","state_url":"https://pith.science/pith/ZNMHH74QF3XFMCAQ3B4DNNHJG6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZNMHH74QF3XFMCAQ3B4DNNHJG6/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":"2026-06-10T14:19:58Z","links":{"resolver":"https://pith.science/pith/ZNMHH74QF3XFMCAQ3B4DNNHJG6","bundle":"https://pith.science/pith/ZNMHH74QF3XFMCAQ3B4DNNHJG6/bundle.json","state":"https://pith.science/pith/ZNMHH74QF3XFMCAQ3B4DNNHJG6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZNMHH74QF3XFMCAQ3B4DNNHJG6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ZNMHH74QF3XFMCAQ3B4DNNHJG6","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":"066596d51cf2d7e5e84ac07d4a3cc98f7cd19143fd13d2cc8446ab98e2d43f9e","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-04T20:45:06Z","title_canon_sha256":"0090848f3c87fd8021372737e6236140a270d6c267f48f3d4fd6cd765734d168"},"schema_version":"1.0","source":{"id":"1803.01417","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.01417","created_at":"2026-05-18T00:13:44Z"},{"alias_kind":"arxiv_version","alias_value":"1803.01417v3","created_at":"2026-05-18T00:13:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.01417","created_at":"2026-05-18T00:13:44Z"},{"alias_kind":"pith_short_12","alias_value":"ZNMHH74QF3XF","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZNMHH74QF3XFMCAQ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZNMHH74Q","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:6446e342b193298c69ed0658a1b78e5b057a1b1321e72049186d716a3906bdb5","target":"graph","created_at":"2026-05-18T00:13:44Z","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":"High-resolution (HR) magnetic resonance images (MRI) provide detailed anatomical information important for clinical application and quantitative image analysis. However, HR MRI conventionally comes at the cost of longer scan time, smaller spatial coverage, and lower signal-to-noise ratio (SNR). Recent studies have shown that single image super-resolution (SISR), a technique to recover HR details from one single low-resolution (LR) input image, could provide high-quality image details with the help of advanced deep convolutional neural networks (CNN). However, deep neural networks consume memor","authors_text":"Anthony G. Christodoulou, Debiao Li, Feng Shi, Yibin Xie, Yuhua Chen, ZhengWei Zhou","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-04T20:45:06Z","title":"Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.01417","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:cd4bd3b504f8016e140b089c31bfccff62dd6b2ca4726508a654546cf6027f03","target":"record","created_at":"2026-05-18T00:13:44Z","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":"066596d51cf2d7e5e84ac07d4a3cc98f7cd19143fd13d2cc8446ab98e2d43f9e","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-04T20:45:06Z","title_canon_sha256":"0090848f3c87fd8021372737e6236140a270d6c267f48f3d4fd6cd765734d168"},"schema_version":"1.0","source":{"id":"1803.01417","kind":"arxiv","version":3}},"canonical_sha256":"cb5873ff902eee560810d87836b4e937a58cf32cadd168f0b532b581fd34efd7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb5873ff902eee560810d87836b4e937a58cf32cadd168f0b532b581fd34efd7","first_computed_at":"2026-05-18T00:13:44.687728Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:44.687728Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nMkVxGaPNg087c+LsX+pKI9iZOsj2dhQ85TZ11egm/m0b6yMF0skhRlsRDfbWKWqC/SdvodBOQLQTbMrpKjlDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:44.688503Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.01417","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cd4bd3b504f8016e140b089c31bfccff62dd6b2ca4726508a654546cf6027f03","sha256:6446e342b193298c69ed0658a1b78e5b057a1b1321e72049186d716a3906bdb5"],"state_sha256":"4ad9b44fcea63012541287442edf071419fae053b408199b6fbdb1598ccb20fc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2tkU6sgPGMegvW+QFlwjthTml0Id+vLpn+mEzqsUlXFsf+1tD+NnTajWOO/ib5w3zsR9ZHggI6bqr/J8IeBwDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T14:19:58.930831Z","bundle_sha256":"360818782243e18a243ba8c5b7bde1523401734a8f8a2142b3dfef06e9f8b5b9"}}