{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:AHNGTUUNLBWOVORYEXVNXYSQU6","short_pith_number":"pith:AHNGTUUN","canonical_record":{"source":{"id":"1907.01268","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-02T09:57:15Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"642f2aa5c72352cf0ed72a69d669a7dbfe54f60bc7d0e86007c321fa6598fcc2","abstract_canon_sha256":"f5815213b0287d58edacb4608c2cb5f4bbd1f9b2f2a82a142bf99d5afae741e9"},"schema_version":"1.0"},"canonical_sha256":"01da69d28d586ceaba3825eadbe250a7b2f615035a6622abd33fb3a9160aafe8","source":{"kind":"arxiv","id":"1907.01268","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.01268","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"arxiv_version","alias_value":"1907.01268v2","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01268","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"pith_short_12","alias_value":"AHNGTUUNLBWO","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"pith_short_16","alias_value":"AHNGTUUNLBWOVORY","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"pith_short_8","alias_value":"AHNGTUUN","created_at":"2026-07-05T01:15:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:AHNGTUUNLBWOVORYEXVNXYSQU6","target":"record","payload":{"canonical_record":{"source":{"id":"1907.01268","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-02T09:57:15Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"642f2aa5c72352cf0ed72a69d669a7dbfe54f60bc7d0e86007c321fa6598fcc2","abstract_canon_sha256":"f5815213b0287d58edacb4608c2cb5f4bbd1f9b2f2a82a142bf99d5afae741e9"},"schema_version":"1.0"},"canonical_sha256":"01da69d28d586ceaba3825eadbe250a7b2f615035a6622abd33fb3a9160aafe8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:15:22.446465Z","signature_b64":"9p6QLm4I//mPY15sibFBL7Uy4sF1oeUti4TvQsZa0fTAQait4dYqT5SGZMB5d4TcDP/xNX5B/nZ5h5RPgOknBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"01da69d28d586ceaba3825eadbe250a7b2f615035a6622abd33fb3a9160aafe8","last_reissued_at":"2026-07-05T01:15:22.446074Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:15:22.446074Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.01268","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:15:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2qrbiCTRDxz6qC8scIpxslZEw9M/kK+7vog3z0SE/HyJuxBhAc00wYtlLIxK6i+nZwAwD7ucyv/cGYdek5BVAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:06:14.094940Z"},"content_sha256":"6a9cae6e2b0e771c39295bcca7cf67e7a63ed20c38a5e92436ffbfdbfdfa29aa","schema_version":"1.0","event_id":"sha256:6a9cae6e2b0e771c39295bcca7cf67e7a63ed20c38a5e92436ffbfdbfdfa29aa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:AHNGTUUNLBWOVORYEXVNXYSQU6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving the generalizability of convolutional neural network-based segmentation on CMR images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Aaron M. Lee, Anish N. Bhuva, Charlotte Manisty, Chen Chen, Daniel Rueckert, Elena Lukaschuk, James C. Moon, Jose Miguel Paiva, Kenneth Fung, Mihir M. Sanghvi, Nay Aung, Rhodri H. Davies, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Wenjia Bai","submitted_at":"2019-07-02T09:57:15Z","abstract_excerpt":"Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g. same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strateg"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01268","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1907.01268/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:15:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"68f+jWx3UH5zstTaahZ4vqdljX0bMBGLX6mMUd8zjM0U7cRohvBCU0WmO5l3vCp47mrVkm9cxluFop9sbSwIAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:06:14.095634Z"},"content_sha256":"07703d7fa97c6697a2772709078a94b1b5efc5f132c6458f15dd73fceba806e1","schema_version":"1.0","event_id":"sha256:07703d7fa97c6697a2772709078a94b1b5efc5f132c6458f15dd73fceba806e1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AHNGTUUNLBWOVORYEXVNXYSQU6/bundle.json","state_url":"https://pith.science/pith/AHNGTUUNLBWOVORYEXVNXYSQU6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AHNGTUUNLBWOVORYEXVNXYSQU6/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":"2026-07-05T15:06:14Z","links":{"resolver":"https://pith.science/pith/AHNGTUUNLBWOVORYEXVNXYSQU6","bundle":"https://pith.science/pith/AHNGTUUNLBWOVORYEXVNXYSQU6/bundle.json","state":"https://pith.science/pith/AHNGTUUNLBWOVORYEXVNXYSQU6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AHNGTUUNLBWOVORYEXVNXYSQU6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:AHNGTUUNLBWOVORYEXVNXYSQU6","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":"f5815213b0287d58edacb4608c2cb5f4bbd1f9b2f2a82a142bf99d5afae741e9","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-02T09:57:15Z","title_canon_sha256":"642f2aa5c72352cf0ed72a69d669a7dbfe54f60bc7d0e86007c321fa6598fcc2"},"schema_version":"1.0","source":{"id":"1907.01268","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.01268","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"arxiv_version","alias_value":"1907.01268v2","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01268","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"pith_short_12","alias_value":"AHNGTUUNLBWO","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"pith_short_16","alias_value":"AHNGTUUNLBWOVORY","created_at":"2026-07-05T01:15:22Z"},{"alias_kind":"pith_short_8","alias_value":"AHNGTUUN","created_at":"2026-07-05T01:15:22Z"}],"graph_snapshots":[{"event_id":"sha256:07703d7fa97c6697a2772709078a94b1b5efc5f132c6458f15dd73fceba806e1","target":"graph","created_at":"2026-07-05T01:15:22Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1907.01268/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g. same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strateg","authors_text":"Aaron M. Lee, Anish N. Bhuva, Charlotte Manisty, Chen Chen, Daniel Rueckert, Elena Lukaschuk, James C. Moon, Jose Miguel Paiva, Kenneth Fung, Mihir M. Sanghvi, Nay Aung, Rhodri H. Davies, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Wenjia Bai","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-02T09:57:15Z","title":"Improving the generalizability of convolutional neural network-based segmentation on CMR images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01268","kind":"arxiv","version":2},"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":"sha256:6a9cae6e2b0e771c39295bcca7cf67e7a63ed20c38a5e92436ffbfdbfdfa29aa","target":"record","created_at":"2026-07-05T01:15:22Z","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":"f5815213b0287d58edacb4608c2cb5f4bbd1f9b2f2a82a142bf99d5afae741e9","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-02T09:57:15Z","title_canon_sha256":"642f2aa5c72352cf0ed72a69d669a7dbfe54f60bc7d0e86007c321fa6598fcc2"},"schema_version":"1.0","source":{"id":"1907.01268","kind":"arxiv","version":2}},"canonical_sha256":"01da69d28d586ceaba3825eadbe250a7b2f615035a6622abd33fb3a9160aafe8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"01da69d28d586ceaba3825eadbe250a7b2f615035a6622abd33fb3a9160aafe8","first_computed_at":"2026-07-05T01:15:22.446074Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:15:22.446074Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9p6QLm4I//mPY15sibFBL7Uy4sF1oeUti4TvQsZa0fTAQait4dYqT5SGZMB5d4TcDP/xNX5B/nZ5h5RPgOknBA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:15:22.446465Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.01268","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6a9cae6e2b0e771c39295bcca7cf67e7a63ed20c38a5e92436ffbfdbfdfa29aa","sha256:07703d7fa97c6697a2772709078a94b1b5efc5f132c6458f15dd73fceba806e1"],"state_sha256":"9c4d8de44ac89bc8b401aefd5f2b4edad108b562ebb26fa938588120882b970f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EBo3SLbJrJkH+HtMhzHtOHe0T9rj0Yuvl4cBmG8kstr6/p+YPJ4uNlqe2bLYblrbWmHLe27cNBDUTuAKzY7hDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T15:06:14.099349Z","bundle_sha256":"97d3fe49bee96ef773361510cb6e10fe937152a3118eb9e7c217bdeb42fd3c23"}}