{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ICLG42WCKCK7H3OMGWFJCWQIW5","short_pith_number":"pith:ICLG42WC","canonical_record":{"source":{"id":"1808.03844","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T18:10:22Z","cross_cats_sorted":[],"title_canon_sha256":"fe24b819fc3cf38989836851982da3d82861054d0614fde7d140b98cce99c512","abstract_canon_sha256":"f1d11ed1ef22a79206e87bcbd29be68ff8c4ccd557d8849c9ab353037b6cb49e"},"schema_version":"1.0"},"canonical_sha256":"40966e6ac25095f3edcc358a915a08b763c176c84046ed6690a7737b13284989","source":{"kind":"arxiv","id":"1808.03844","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.03844","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"arxiv_version","alias_value":"1808.03844v1","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.03844","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"pith_short_12","alias_value":"ICLG42WCKCK7","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"ICLG42WCKCK7H3OM","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"ICLG42WC","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ICLG42WCKCK7H3OMGWFJCWQIW5","target":"record","payload":{"canonical_record":{"source":{"id":"1808.03844","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T18:10:22Z","cross_cats_sorted":[],"title_canon_sha256":"fe24b819fc3cf38989836851982da3d82861054d0614fde7d140b98cce99c512","abstract_canon_sha256":"f1d11ed1ef22a79206e87bcbd29be68ff8c4ccd557d8849c9ab353037b6cb49e"},"schema_version":"1.0"},"canonical_sha256":"40966e6ac25095f3edcc358a915a08b763c176c84046ed6690a7737b13284989","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:01:07.000277Z","signature_b64":"WZ530FaRauuEAU7hg1sowQYlPj6d27gmcvCWY+ix3WqgMOsgG0wWu80+3V5VyZ7hOkcBnoaKE+W6TOxkEVhTAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40966e6ac25095f3edcc358a915a08b763c176c84046ed6690a7737b13284989","last_reissued_at":"2026-05-18T00:01:06.999599Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:01:06.999599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.03844","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":"2026-05-18T00:01:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a+O3GzRQ99b245cv+CmKzkRHCkQWT4SnlYUkmKnF83yqmuv8ysKXSvCjLOS1SSI5Y3xaZIXVQbWf6KXZDF87BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:01:54.904128Z"},"content_sha256":"e403beb4d4b865ffb7777e26e6c82acd4d5d5062d57aeb6847632899580734c0","schema_version":"1.0","event_id":"sha256:e403beb4d4b865ffb7777e26e6c82acd4d5d5062d57aeb6847632899580734c0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ICLG42WCKCK7H3OMGWFJCWQIW5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ana Babic, Bradley Wright, Brian Wolpin, Caitlin Zellers, Christopher P. Bridge, Fabian Troschel, Florian Fintelmann, Gopal Kotecha, Katherine Andriole, Khanant Desai, Lauren Brais, Marisa Welch, Mark Michalski, Michael Rosenthal, Natalia Khalaf, Neil Tenenholtz, Nityanand Miskin, William Wrobel","submitted_at":"2018-08-11T18:10:22Z","abstract_excerpt":"The amounts of muscle and fat in a person's body, known as body composition, are correlated with cancer risks, cancer survival, and cardiovascular risk. The current gold standard for measuring body composition requires time-consuming manual segmentation of CT images by an expert reader. In this work, we describe a two-step process to fully automate the analysis of CT body composition using a DenseNet to select the CT slice and U-Net to perform segmentation. We train and test our methods on independent cohorts. Our results show Dice scores (0.95-0.98) and correlation coefficients (R=0.99) that "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.03844","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":"2026-05-18T00:01:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AhQpBhE4+NcFS1q7JZiz/wJaNEtlxwgDr2mFn3uzLycL2GvzuNJA4KZsMuIIJT+Dx31iaoSLdhmsR/qR9us/Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T15:01:54.904922Z"},"content_sha256":"584e60870207ee3f07f683f95a214b6f990971d1367ff5a317812d15c6833d8c","schema_version":"1.0","event_id":"sha256:584e60870207ee3f07f683f95a214b6f990971d1367ff5a317812d15c6833d8c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ICLG42WCKCK7H3OMGWFJCWQIW5/bundle.json","state_url":"https://pith.science/pith/ICLG42WCKCK7H3OMGWFJCWQIW5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ICLG42WCKCK7H3OMGWFJCWQIW5/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":"2026-05-31T15:01:54Z","links":{"resolver":"https://pith.science/pith/ICLG42WCKCK7H3OMGWFJCWQIW5","bundle":"https://pith.science/pith/ICLG42WCKCK7H3OMGWFJCWQIW5/bundle.json","state":"https://pith.science/pith/ICLG42WCKCK7H3OMGWFJCWQIW5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ICLG42WCKCK7H3OMGWFJCWQIW5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ICLG42WCKCK7H3OMGWFJCWQIW5","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":"f1d11ed1ef22a79206e87bcbd29be68ff8c4ccd557d8849c9ab353037b6cb49e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T18:10:22Z","title_canon_sha256":"fe24b819fc3cf38989836851982da3d82861054d0614fde7d140b98cce99c512"},"schema_version":"1.0","source":{"id":"1808.03844","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.03844","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"arxiv_version","alias_value":"1808.03844v1","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.03844","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"pith_short_12","alias_value":"ICLG42WCKCK7","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"ICLG42WCKCK7H3OM","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"ICLG42WC","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:584e60870207ee3f07f683f95a214b6f990971d1367ff5a317812d15c6833d8c","target":"graph","created_at":"2026-05-18T00:01:06Z","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":"The amounts of muscle and fat in a person's body, known as body composition, are correlated with cancer risks, cancer survival, and cardiovascular risk. The current gold standard for measuring body composition requires time-consuming manual segmentation of CT images by an expert reader. In this work, we describe a two-step process to fully automate the analysis of CT body composition using a DenseNet to select the CT slice and U-Net to perform segmentation. We train and test our methods on independent cohorts. Our results show Dice scores (0.95-0.98) and correlation coefficients (R=0.99) that ","authors_text":"Ana Babic, Bradley Wright, Brian Wolpin, Caitlin Zellers, Christopher P. Bridge, Fabian Troschel, Florian Fintelmann, Gopal Kotecha, Katherine Andriole, Khanant Desai, Lauren Brais, Marisa Welch, Mark Michalski, Michael Rosenthal, Natalia Khalaf, Neil Tenenholtz, Nityanand Miskin, William Wrobel","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T18:10:22Z","title":"Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.03844","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:e403beb4d4b865ffb7777e26e6c82acd4d5d5062d57aeb6847632899580734c0","target":"record","created_at":"2026-05-18T00:01:06Z","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":"f1d11ed1ef22a79206e87bcbd29be68ff8c4ccd557d8849c9ab353037b6cb49e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T18:10:22Z","title_canon_sha256":"fe24b819fc3cf38989836851982da3d82861054d0614fde7d140b98cce99c512"},"schema_version":"1.0","source":{"id":"1808.03844","kind":"arxiv","version":1}},"canonical_sha256":"40966e6ac25095f3edcc358a915a08b763c176c84046ed6690a7737b13284989","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40966e6ac25095f3edcc358a915a08b763c176c84046ed6690a7737b13284989","first_computed_at":"2026-05-18T00:01:06.999599Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:01:06.999599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WZ530FaRauuEAU7hg1sowQYlPj6d27gmcvCWY+ix3WqgMOsgG0wWu80+3V5VyZ7hOkcBnoaKE+W6TOxkEVhTAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:01:07.000277Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.03844","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e403beb4d4b865ffb7777e26e6c82acd4d5d5062d57aeb6847632899580734c0","sha256:584e60870207ee3f07f683f95a214b6f990971d1367ff5a317812d15c6833d8c"],"state_sha256":"74233042f5ff0da1f2acdf468ca997eaf04f769ab6416d1645c29fde8cdaf227"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J4s/v8ZNBwPVVwO7d3FoZopqoZcz/SndeBfOM+SUUAmvSOQBy84Py9iNr8z/T9TEzhrspyFKMYL/nUf9j8DKAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T15:01:54.909599Z","bundle_sha256":"7e8a974b918f231535e65ebe6d3f5ef3c3cf6909158113b776dcef4670802b8c"}}