{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4A53RZLNMU7EL2DRICY6XNFHTI","short_pith_number":"pith:4A53RZLN","canonical_record":{"source":{"id":"1906.10400","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-25T09:15:24Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"0ae37a6fac8d4d2bb75849e235e1d4d8e61101aacec56f21e1cd41b45a0040a9","abstract_canon_sha256":"f56a54e51f7104221298a2923930d99836232423224aa07ccc567b6a138ca80a"},"schema_version":"1.0"},"canonical_sha256":"e03bb8e56d653e45e87140b1ebb4a79a010554977870bd57c56e09f449df4e7d","source":{"kind":"arxiv","id":"1906.10400","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.10400","created_at":"2026-05-17T23:42:18Z"},{"alias_kind":"arxiv_version","alias_value":"1906.10400v1","created_at":"2026-05-17T23:42:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.10400","created_at":"2026-05-17T23:42:18Z"},{"alias_kind":"pith_short_12","alias_value":"4A53RZLNMU7E","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4A53RZLNMU7EL2DR","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4A53RZLN","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4A53RZLNMU7EL2DRICY6XNFHTI","target":"record","payload":{"canonical_record":{"source":{"id":"1906.10400","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-25T09:15:24Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"0ae37a6fac8d4d2bb75849e235e1d4d8e61101aacec56f21e1cd41b45a0040a9","abstract_canon_sha256":"f56a54e51f7104221298a2923930d99836232423224aa07ccc567b6a138ca80a"},"schema_version":"1.0"},"canonical_sha256":"e03bb8e56d653e45e87140b1ebb4a79a010554977870bd57c56e09f449df4e7d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:18.169288Z","signature_b64":"1AAlMDIMSTcIsoR7BWAXhDY//C+MaeuhrZKcc083p7ZcwIrqtFjfPBvnz+xSW2n3l0pLB4d9kXccNzOd3ERnDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e03bb8e56d653e45e87140b1ebb4a79a010554977870bd57c56e09f449df4e7d","last_reissued_at":"2026-05-17T23:42:18.168834Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:18.168834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.10400","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l4GFhxaHpKEODr9vjAg9E70tnylpTE5z1wpA2wCReZ9zIQvzwUALl43eH4rr2oD70XE/oGDGHcyZHiP8jCuHAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-18T23:50:34.461197Z"},"content_sha256":"758016fd421bfa4e2d0d97d079672ed4578af6e321757382abea7aa0d3797180","schema_version":"1.0","event_id":"sha256:758016fd421bfa4e2d0d97d079672ed4578af6e321757382abea7aa0d3797180"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4A53RZLNMU7EL2DRICY6XNFHTI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Dinggang Shen, Lichi Zhang, Qian Wang, Xuhua Ren","submitted_at":"2019-06-25T09:15:24Z","abstract_excerpt":"Medical image segmentation is challenging especially in dealing with small dataset of 3D MR images. Encoding the variation of brain anatomical struc-tures from individual subjects cannot be easily achieved, which is further chal-lenged by only a limited number of well labeled subjects for training. In this study, we aim to address the issue of brain MR image segmentation in small da-taset. First, concerning the limited number of training images, we adopt adver-sarial defense to augment the training data and therefore increase the robustness of the network. Second, inspired by the prior knowled"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.10400","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BcXZePcrorF/ZvZ2khR9j8Rr/CCxG6D8JGrpb+gjCpwq04pMzabMya9kQ83MieSNh+hWaa1iU0JLM2w1+8ikDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-18T23:50:34.461807Z"},"content_sha256":"8a156803c22e1a5a514cdcdf971753dbe82bb5950155e343e27dcc6f22c1fdf4","schema_version":"1.0","event_id":"sha256:8a156803c22e1a5a514cdcdf971753dbe82bb5950155e343e27dcc6f22c1fdf4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4A53RZLNMU7EL2DRICY6XNFHTI/bundle.json","state_url":"https://pith.science/pith/4A53RZLNMU7EL2DRICY6XNFHTI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4A53RZLNMU7EL2DRICY6XNFHTI/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":"2026-05-18T23:50:34Z","links":{"resolver":"https://pith.science/pith/4A53RZLNMU7EL2DRICY6XNFHTI","bundle":"https://pith.science/pith/4A53RZLNMU7EL2DRICY6XNFHTI/bundle.json","state":"https://pith.science/pith/4A53RZLNMU7EL2DRICY6XNFHTI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4A53RZLNMU7EL2DRICY6XNFHTI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4A53RZLNMU7EL2DRICY6XNFHTI","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":"f56a54e51f7104221298a2923930d99836232423224aa07ccc567b6a138ca80a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-25T09:15:24Z","title_canon_sha256":"0ae37a6fac8d4d2bb75849e235e1d4d8e61101aacec56f21e1cd41b45a0040a9"},"schema_version":"1.0","source":{"id":"1906.10400","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.10400","created_at":"2026-05-17T23:42:18Z"},{"alias_kind":"arxiv_version","alias_value":"1906.10400v1","created_at":"2026-05-17T23:42:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.10400","created_at":"2026-05-17T23:42:18Z"},{"alias_kind":"pith_short_12","alias_value":"4A53RZLNMU7E","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4A53RZLNMU7EL2DR","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4A53RZLN","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:8a156803c22e1a5a514cdcdf971753dbe82bb5950155e343e27dcc6f22c1fdf4","target":"graph","created_at":"2026-05-17T23:42:18Z","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":"Medical image segmentation is challenging especially in dealing with small dataset of 3D MR images. Encoding the variation of brain anatomical struc-tures from individual subjects cannot be easily achieved, which is further chal-lenged by only a limited number of well labeled subjects for training. In this study, we aim to address the issue of brain MR image segmentation in small da-taset. First, concerning the limited number of training images, we adopt adver-sarial defense to augment the training data and therefore increase the robustness of the network. Second, inspired by the prior knowled","authors_text":"Dinggang Shen, Lichi Zhang, Qian Wang, Xuhua Ren","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-25T09:15:24Z","title":"Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.10400","kind":"arxiv","version":1},"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":"sha256:758016fd421bfa4e2d0d97d079672ed4578af6e321757382abea7aa0d3797180","target":"record","created_at":"2026-05-17T23:42:18Z","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":"f56a54e51f7104221298a2923930d99836232423224aa07ccc567b6a138ca80a","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-25T09:15:24Z","title_canon_sha256":"0ae37a6fac8d4d2bb75849e235e1d4d8e61101aacec56f21e1cd41b45a0040a9"},"schema_version":"1.0","source":{"id":"1906.10400","kind":"arxiv","version":1}},"canonical_sha256":"e03bb8e56d653e45e87140b1ebb4a79a010554977870bd57c56e09f449df4e7d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e03bb8e56d653e45e87140b1ebb4a79a010554977870bd57c56e09f449df4e7d","first_computed_at":"2026-05-17T23:42:18.168834Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:18.168834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1AAlMDIMSTcIsoR7BWAXhDY//C+MaeuhrZKcc083p7ZcwIrqtFjfPBvnz+xSW2n3l0pLB4d9kXccNzOd3ERnDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:18.169288Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.10400","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:758016fd421bfa4e2d0d97d079672ed4578af6e321757382abea7aa0d3797180","sha256:8a156803c22e1a5a514cdcdf971753dbe82bb5950155e343e27dcc6f22c1fdf4"],"state_sha256":"9c48c122214c88fc207251c434137b3a1919f0d13b5ce16c7d69f5e910093425"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IoAmZNe+i+pOaOVlwzdGK6Djk5PD5S6ZJUat81kOAWCJM0ZKNrcLMDkbNhFVQ8MMa6/laxfgav9FLF6CCBpYCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-18T23:50:34.463938Z","bundle_sha256":"f4b23caf05a4754bb968f3334e268221278ad35421b36f2c53b7fcdcab0cd27a"}}