{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:LW37O2DO3CQETR5LJNKIJ2DMTM","short_pith_number":"pith:LW37O2DO","canonical_record":{"source":{"id":"1801.08599","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-25T21:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"a191f839a14df7842cef0b61127904abc50cb0b5793839c52cc23132bac919e5","abstract_canon_sha256":"6e34cb8b579ac69e103a7377410260803ff0f33deba714904ba2ed01b9d3b172"},"schema_version":"1.0"},"canonical_sha256":"5db7f7686ed8a049c7ab4b5484e86c9b1ab86970d8c65ffb8e8efe3c0a4795e9","source":{"kind":"arxiv","id":"1801.08599","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.08599","created_at":"2026-05-18T00:25:03Z"},{"alias_kind":"arxiv_version","alias_value":"1801.08599v1","created_at":"2026-05-18T00:25:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.08599","created_at":"2026-05-18T00:25:03Z"},{"alias_kind":"pith_short_12","alias_value":"LW37O2DO3CQE","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"LW37O2DO3CQETR5L","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"LW37O2DO","created_at":"2026-05-18T12:32:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:LW37O2DO3CQETR5LJNKIJ2DMTM","target":"record","payload":{"canonical_record":{"source":{"id":"1801.08599","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-25T21:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"a191f839a14df7842cef0b61127904abc50cb0b5793839c52cc23132bac919e5","abstract_canon_sha256":"6e34cb8b579ac69e103a7377410260803ff0f33deba714904ba2ed01b9d3b172"},"schema_version":"1.0"},"canonical_sha256":"5db7f7686ed8a049c7ab4b5484e86c9b1ab86970d8c65ffb8e8efe3c0a4795e9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:03.493516Z","signature_b64":"QaqTjE3M0fXdlxfsC6/wgnncG+bBOKQay5uWWjelQACmKD41uONz1Xjv8SepJ35RVSk0chX0ii4gMS83JpKrDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5db7f7686ed8a049c7ab4b5484e86c9b1ab86970d8c65ffb8e8efe3c0a4795e9","last_reissued_at":"2026-05-18T00:25:03.493051Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:03.493051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.08599","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":"2026-05-18T00:25:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j3oaBCmaCTUr++/WL049fB+byEVOqRVq4ZBLPvHGQRwo2LwqOSzWj/zqdfdtc01Zm4AfL4JpPvQ++3zc345WBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T22:03:30.685533Z"},"content_sha256":"04f2ecb89222b66b56df07e3e60d15ddb1d12a8af6e4cd9e46e7d58bd202c417","schema_version":"1.0","event_id":"sha256:04f2ecb89222b66b56df07e3e60d15ddb1d12a8af6e4cd9e46e7d58bd202c417"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:LW37O2DO3CQETR5LJNKIJ2DMTM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jianhua Yao, Le Lu, Ling Zhang, Milan Sonka, Mohammadhadi Bagheri, Ronald M. Summers, Zhihui Guo","submitted_at":"2018-01-25T21:34:44Z","abstract_excerpt":"This paper reports Deep LOGISMOS approach to 3D tumor segmentation by incorporating boundary information derived from deep contextual learning to LOGISMOS - layered optimal graph image segmentation of multiple objects and surfaces. Accurate and reliable tumor segmentation is essential to tumor growth analysis and treatment selection. A fully convolutional network (FCN), UNet, is first trained using three adjacent 2D patches centered at the tumor, providing contextual UNet segmentation and probability map for each 2D patch. The UNet segmentation is then refined by Gaussian Mixture Model (GMM) a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.08599","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":"2026-05-18T00:25:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3pFDdr8zNve98Pbf4yGnaxoAjza4achsAK1EGaLnupIJMgPBfTsm4123n3+8Xbk4YJrZR7bijU5ITR8bo1N4DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T22:03:30.685888Z"},"content_sha256":"fb9f016e482c0c6b9b0a56365db5d59cb212acc65ec439b9c7f943a8c082b743","schema_version":"1.0","event_id":"sha256:fb9f016e482c0c6b9b0a56365db5d59cb212acc65ec439b9c7f943a8c082b743"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LW37O2DO3CQETR5LJNKIJ2DMTM/bundle.json","state_url":"https://pith.science/pith/LW37O2DO3CQETR5LJNKIJ2DMTM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LW37O2DO3CQETR5LJNKIJ2DMTM/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":"2026-06-20T22:03:30Z","links":{"resolver":"https://pith.science/pith/LW37O2DO3CQETR5LJNKIJ2DMTM","bundle":"https://pith.science/pith/LW37O2DO3CQETR5LJNKIJ2DMTM/bundle.json","state":"https://pith.science/pith/LW37O2DO3CQETR5LJNKIJ2DMTM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LW37O2DO3CQETR5LJNKIJ2DMTM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:LW37O2DO3CQETR5LJNKIJ2DMTM","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":"6e34cb8b579ac69e103a7377410260803ff0f33deba714904ba2ed01b9d3b172","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-25T21:34:44Z","title_canon_sha256":"a191f839a14df7842cef0b61127904abc50cb0b5793839c52cc23132bac919e5"},"schema_version":"1.0","source":{"id":"1801.08599","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.08599","created_at":"2026-05-18T00:25:03Z"},{"alias_kind":"arxiv_version","alias_value":"1801.08599v1","created_at":"2026-05-18T00:25:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.08599","created_at":"2026-05-18T00:25:03Z"},{"alias_kind":"pith_short_12","alias_value":"LW37O2DO3CQE","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"LW37O2DO3CQETR5L","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"LW37O2DO","created_at":"2026-05-18T12:32:37Z"}],"graph_snapshots":[{"event_id":"sha256:fb9f016e482c0c6b9b0a56365db5d59cb212acc65ec439b9c7f943a8c082b743","target":"graph","created_at":"2026-05-18T00:25:03Z","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":"This paper reports Deep LOGISMOS approach to 3D tumor segmentation by incorporating boundary information derived from deep contextual learning to LOGISMOS - layered optimal graph image segmentation of multiple objects and surfaces. Accurate and reliable tumor segmentation is essential to tumor growth analysis and treatment selection. A fully convolutional network (FCN), UNet, is first trained using three adjacent 2D patches centered at the tumor, providing contextual UNet segmentation and probability map for each 2D patch. The UNet segmentation is then refined by Gaussian Mixture Model (GMM) a","authors_text":"Jianhua Yao, Le Lu, Ling Zhang, Milan Sonka, Mohammadhadi Bagheri, Ronald M. Summers, Zhihui Guo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-25T21:34:44Z","title":"Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.08599","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":"sha256:04f2ecb89222b66b56df07e3e60d15ddb1d12a8af6e4cd9e46e7d58bd202c417","target":"record","created_at":"2026-05-18T00:25:03Z","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":"6e34cb8b579ac69e103a7377410260803ff0f33deba714904ba2ed01b9d3b172","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-25T21:34:44Z","title_canon_sha256":"a191f839a14df7842cef0b61127904abc50cb0b5793839c52cc23132bac919e5"},"schema_version":"1.0","source":{"id":"1801.08599","kind":"arxiv","version":1}},"canonical_sha256":"5db7f7686ed8a049c7ab4b5484e86c9b1ab86970d8c65ffb8e8efe3c0a4795e9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5db7f7686ed8a049c7ab4b5484e86c9b1ab86970d8c65ffb8e8efe3c0a4795e9","first_computed_at":"2026-05-18T00:25:03.493051Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:25:03.493051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QaqTjE3M0fXdlxfsC6/wgnncG+bBOKQay5uWWjelQACmKD41uONz1Xjv8SepJ35RVSk0chX0ii4gMS83JpKrDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:25:03.493516Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.08599","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:04f2ecb89222b66b56df07e3e60d15ddb1d12a8af6e4cd9e46e7d58bd202c417","sha256:fb9f016e482c0c6b9b0a56365db5d59cb212acc65ec439b9c7f943a8c082b743"],"state_sha256":"a6bb8079159ac2e8f38e2a0a7e603c3cf1e927a5f8c09537e57eaa38e8b77021"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JKHrbBdsOD6V/YYWOONRNBW73u4D8WR84Q0B7i39HD+ul014gG5RO/d9tRsDogpBQ5hrwV0S+c8pTeeB6XjbAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-20T22:03:30.687903Z","bundle_sha256":"0461cbcebf2be2495e210bb2a2e924ed1733bd0b5b8a24def1514a66a5ac11e0"}}