{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:KJDXFM5VAY56WCPPURQJBR7LKI","short_pith_number":"pith:KJDXFM5V","canonical_record":{"source":{"id":"1810.05732","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-11T04:03:30Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"d9bd81e36f04eacf54afdb9ebf67acc8dda0c20d61f3bfdb093b004cff58c97b","abstract_canon_sha256":"8135364344b92b08a6cf0d176a9256c7c6d88a0d04e437965730de16c2dfc329"},"schema_version":"1.0"},"canonical_sha256":"524772b3b5063beb09efa46090c7eb5228a2320c81de3eed65eb67583116a9a3","source":{"kind":"arxiv","id":"1810.05732","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.05732","created_at":"2026-05-18T00:03:27Z"},{"alias_kind":"arxiv_version","alias_value":"1810.05732v1","created_at":"2026-05-18T00:03:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.05732","created_at":"2026-05-18T00:03:27Z"},{"alias_kind":"pith_short_12","alias_value":"KJDXFM5VAY56","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KJDXFM5VAY56WCPP","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KJDXFM5V","created_at":"2026-05-18T12:32:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:KJDXFM5VAY56WCPPURQJBR7LKI","target":"record","payload":{"canonical_record":{"source":{"id":"1810.05732","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-11T04:03:30Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"d9bd81e36f04eacf54afdb9ebf67acc8dda0c20d61f3bfdb093b004cff58c97b","abstract_canon_sha256":"8135364344b92b08a6cf0d176a9256c7c6d88a0d04e437965730de16c2dfc329"},"schema_version":"1.0"},"canonical_sha256":"524772b3b5063beb09efa46090c7eb5228a2320c81de3eed65eb67583116a9a3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:27.094947Z","signature_b64":"hRCB3kx40FMtVT2ZP4N/BewcyFNkn2XGrTFnWanoDQdAobo62Sd1jsMb3zxNZWsfjhoqDvQRTlL/dg5fDKPuBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"524772b3b5063beb09efa46090c7eb5228a2320c81de3eed65eb67583116a9a3","last_reissued_at":"2026-05-18T00:03:27.094547Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:27.094547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.05732","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":"2026-05-18T00:03:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z8y2X023Qfkyo92PMbVbvRtCrsU110HKpunzSpd76+NCVgeS1sq+ewcQPNuxGZaVuHZB7JSDugf8ca5iyD+ABQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T12:35:38.478565Z"},"content_sha256":"d4b738323e2752b842210d2ef35dbaae7b270b8aecf2adbfda23076e53aec704","schema_version":"1.0","event_id":"sha256:d4b738323e2752b842210d2ef35dbaae7b270b8aecf2adbfda23076e53aec704"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:KJDXFM5VAY56WCPPURQJBR7LKI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Novel Domain Adaptation Framework for Medical Image Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CV","authors_text":"Amir Gholami, George Biros, Kurt Keutzer, Naveen Himthani, Peter Jin, Shashank Subramanian, Sicheng Zhao, Varun Shenoy, Xiangyu Yue","submitted_at":"2018-10-11T04:03:30Z","abstract_excerpt":"We propose a segmentation framework that uses deep neural networks and introduce two innovations. First, we describe a biophysics-based domain adaptation method. Second, we propose an automatic method to segment white and gray matter, and cerebrospinal fluid, in addition to tumorous tissue. Regarding our first innovation, we use a domain adaptation framework that combines a novel multispecies biophysical tumor growth model with a generative adversarial model to create realistic looking synthetic multimodal MR images with known segmentation. Regarding our second innovation, we propose an automa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.05732","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":"2026-05-18T00:03:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h6kNhKDl8pAS8iF1YTRQ3cHAOoIQlDOo7MzDtXwvf2vM3WKHvSMH3AFxTHClAcolq3QmOhCioRZZAqGpWJ6uCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T12:35:38.478914Z"},"content_sha256":"c81c80d73b667c04a28c3564c142cbcf70b00a1349e86a68add44c3e80d99b33","schema_version":"1.0","event_id":"sha256:c81c80d73b667c04a28c3564c142cbcf70b00a1349e86a68add44c3e80d99b33"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KJDXFM5VAY56WCPPURQJBR7LKI/bundle.json","state_url":"https://pith.science/pith/KJDXFM5VAY56WCPPURQJBR7LKI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KJDXFM5VAY56WCPPURQJBR7LKI/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":"2026-05-28T12:35:38Z","links":{"resolver":"https://pith.science/pith/KJDXFM5VAY56WCPPURQJBR7LKI","bundle":"https://pith.science/pith/KJDXFM5VAY56WCPPURQJBR7LKI/bundle.json","state":"https://pith.science/pith/KJDXFM5VAY56WCPPURQJBR7LKI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KJDXFM5VAY56WCPPURQJBR7LKI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:KJDXFM5VAY56WCPPURQJBR7LKI","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":"8135364344b92b08a6cf0d176a9256c7c6d88a0d04e437965730de16c2dfc329","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-11T04:03:30Z","title_canon_sha256":"d9bd81e36f04eacf54afdb9ebf67acc8dda0c20d61f3bfdb093b004cff58c97b"},"schema_version":"1.0","source":{"id":"1810.05732","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.05732","created_at":"2026-05-18T00:03:27Z"},{"alias_kind":"arxiv_version","alias_value":"1810.05732v1","created_at":"2026-05-18T00:03:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.05732","created_at":"2026-05-18T00:03:27Z"},{"alias_kind":"pith_short_12","alias_value":"KJDXFM5VAY56","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KJDXFM5VAY56WCPP","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KJDXFM5V","created_at":"2026-05-18T12:32:33Z"}],"graph_snapshots":[{"event_id":"sha256:c81c80d73b667c04a28c3564c142cbcf70b00a1349e86a68add44c3e80d99b33","target":"graph","created_at":"2026-05-18T00:03:27Z","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":"We propose a segmentation framework that uses deep neural networks and introduce two innovations. First, we describe a biophysics-based domain adaptation method. Second, we propose an automatic method to segment white and gray matter, and cerebrospinal fluid, in addition to tumorous tissue. Regarding our first innovation, we use a domain adaptation framework that combines a novel multispecies biophysical tumor growth model with a generative adversarial model to create realistic looking synthetic multimodal MR images with known segmentation. Regarding our second innovation, we propose an automa","authors_text":"Amir Gholami, George Biros, Kurt Keutzer, Naveen Himthani, Peter Jin, Shashank Subramanian, Sicheng Zhao, Varun Shenoy, Xiangyu Yue","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-11T04:03:30Z","title":"A Novel Domain Adaptation Framework for Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.05732","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:d4b738323e2752b842210d2ef35dbaae7b270b8aecf2adbfda23076e53aec704","target":"record","created_at":"2026-05-18T00:03:27Z","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":"8135364344b92b08a6cf0d176a9256c7c6d88a0d04e437965730de16c2dfc329","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-11T04:03:30Z","title_canon_sha256":"d9bd81e36f04eacf54afdb9ebf67acc8dda0c20d61f3bfdb093b004cff58c97b"},"schema_version":"1.0","source":{"id":"1810.05732","kind":"arxiv","version":1}},"canonical_sha256":"524772b3b5063beb09efa46090c7eb5228a2320c81de3eed65eb67583116a9a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"524772b3b5063beb09efa46090c7eb5228a2320c81de3eed65eb67583116a9a3","first_computed_at":"2026-05-18T00:03:27.094547Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:03:27.094547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hRCB3kx40FMtVT2ZP4N/BewcyFNkn2XGrTFnWanoDQdAobo62Sd1jsMb3zxNZWsfjhoqDvQRTlL/dg5fDKPuBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:03:27.094947Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.05732","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d4b738323e2752b842210d2ef35dbaae7b270b8aecf2adbfda23076e53aec704","sha256:c81c80d73b667c04a28c3564c142cbcf70b00a1349e86a68add44c3e80d99b33"],"state_sha256":"9220bd91171774dc069b2e80b8873abb6d2b105586da9ba897a7a6e565bfab13"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e8JfannFAq5twGMtnX8xaVGPvRbTQPlkNpuryyICsVmhFZwl3JaHPZtpCEXYbNMJ7tvczREc0N2vVRkE0fmIDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T12:35:38.480895Z","bundle_sha256":"e1b720ac666474904f07964a7995dfcd1bca77ba263ea82d89881f237e097c28"}}