{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:V2MHLAULAR2SMUYU7OHOOZ3NP6","short_pith_number":"pith:V2MHLAUL","canonical_record":{"source":{"id":"1811.10419","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-22T10:19:22Z","cross_cats_sorted":[],"title_canon_sha256":"34d22b7ce7947107710d47301df2689595ab3d8f48bb97bb220d15a3c3c9e0e3","abstract_canon_sha256":"90c656265c32afcf794f443b3f2f80aa2e6c85e9d6eb6a920002e3e957a2a1b6"},"schema_version":"1.0"},"canonical_sha256":"ae9875828b0475265314fb8ee7676d7f9b65b7525b874645adf98cc6387cd11a","source":{"kind":"arxiv","id":"1811.10419","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.10419","created_at":"2026-05-17T23:59:48Z"},{"alias_kind":"arxiv_version","alias_value":"1811.10419v1","created_at":"2026-05-17T23:59:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.10419","created_at":"2026-05-17T23:59:48Z"},{"alias_kind":"pith_short_12","alias_value":"V2MHLAULAR2S","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"V2MHLAULAR2SMUYU","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"V2MHLAUL","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:V2MHLAULAR2SMUYU7OHOOZ3NP6","target":"record","payload":{"canonical_record":{"source":{"id":"1811.10419","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-22T10:19:22Z","cross_cats_sorted":[],"title_canon_sha256":"34d22b7ce7947107710d47301df2689595ab3d8f48bb97bb220d15a3c3c9e0e3","abstract_canon_sha256":"90c656265c32afcf794f443b3f2f80aa2e6c85e9d6eb6a920002e3e957a2a1b6"},"schema_version":"1.0"},"canonical_sha256":"ae9875828b0475265314fb8ee7676d7f9b65b7525b874645adf98cc6387cd11a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:48.001464Z","signature_b64":"11RwqytZOFVfK2780WoTNxGXJSsVCfN21wmLjELq4NQCOQ95ADOfkKhTv2RdRUWirnNxH9S0S+3nYCfd5RI1BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae9875828b0475265314fb8ee7676d7f9b65b7525b874645adf98cc6387cd11a","last_reissued_at":"2026-05-17T23:59:48.000928Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:48.000928Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.10419","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":"2026-05-17T23:59:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ro/vfFc5OwlXZoT3gasLuKbaLfwRHRLGF6vUz6pxZkVanDk+PMqDa5KVdvQFf3teAR+5BOuZAvKJTirzpZ79Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T15:27:32.688744Z"},"content_sha256":"d7ec4664cc2793e59894b7083802d4eaf2ce5fe1b14fb0eee630f1e72a1430ed","schema_version":"1.0","event_id":"sha256:d7ec4664cc2793e59894b7083802d4eaf2ce5fe1b14fb0eee630f1e72a1430ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:V2MHLAULAR2SMUYU7OHOOZ3NP6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christoph Meinel, Haojin Yang, Mina Rezaei","submitted_at":"2018-11-22T10:19:22Z","abstract_excerpt":"We propose a new generative adversarial architecture to mitigate imbalance data problem for the task of medical image semantic segmentation where the majority of pixels belong to a healthy region and few belong to lesion or non-health region. A model trained with imbalanced data tends to bias towards healthy data which is not desired in clinical applications. We design a new conditional GAN with two components: a generative model and a discriminative model to mitigate imbalanced data problem through selective weighted loss. While the generator is trained on sequential magnetic resonance images"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.10419","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":"2026-05-17T23:59:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wzdeKZx3xJyol26SzWuKnvW+GswnEDLNVIpJfAJwHHKUdKh9oQwpXfequRk/t5iQn+aSNtMZvl3hiEzBTjs+BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T15:27:32.689328Z"},"content_sha256":"7923ac6a8147c90e96da3a468eea67d3fca959d35ef5ef71d8e51777146eb9c0","schema_version":"1.0","event_id":"sha256:7923ac6a8147c90e96da3a468eea67d3fca959d35ef5ef71d8e51777146eb9c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V2MHLAULAR2SMUYU7OHOOZ3NP6/bundle.json","state_url":"https://pith.science/pith/V2MHLAULAR2SMUYU7OHOOZ3NP6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V2MHLAULAR2SMUYU7OHOOZ3NP6/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":"2026-05-30T15:27:32Z","links":{"resolver":"https://pith.science/pith/V2MHLAULAR2SMUYU7OHOOZ3NP6","bundle":"https://pith.science/pith/V2MHLAULAR2SMUYU7OHOOZ3NP6/bundle.json","state":"https://pith.science/pith/V2MHLAULAR2SMUYU7OHOOZ3NP6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V2MHLAULAR2SMUYU7OHOOZ3NP6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:V2MHLAULAR2SMUYU7OHOOZ3NP6","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":"90c656265c32afcf794f443b3f2f80aa2e6c85e9d6eb6a920002e3e957a2a1b6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-22T10:19:22Z","title_canon_sha256":"34d22b7ce7947107710d47301df2689595ab3d8f48bb97bb220d15a3c3c9e0e3"},"schema_version":"1.0","source":{"id":"1811.10419","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.10419","created_at":"2026-05-17T23:59:48Z"},{"alias_kind":"arxiv_version","alias_value":"1811.10419v1","created_at":"2026-05-17T23:59:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.10419","created_at":"2026-05-17T23:59:48Z"},{"alias_kind":"pith_short_12","alias_value":"V2MHLAULAR2S","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"V2MHLAULAR2SMUYU","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"V2MHLAUL","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:7923ac6a8147c90e96da3a468eea67d3fca959d35ef5ef71d8e51777146eb9c0","target":"graph","created_at":"2026-05-17T23:59:48Z","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 new generative adversarial architecture to mitigate imbalance data problem for the task of medical image semantic segmentation where the majority of pixels belong to a healthy region and few belong to lesion or non-health region. A model trained with imbalanced data tends to bias towards healthy data which is not desired in clinical applications. We design a new conditional GAN with two components: a generative model and a discriminative model to mitigate imbalanced data problem through selective weighted loss. While the generator is trained on sequential magnetic resonance images","authors_text":"Christoph Meinel, Haojin Yang, Mina Rezaei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-22T10:19:22Z","title":"Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.10419","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:d7ec4664cc2793e59894b7083802d4eaf2ce5fe1b14fb0eee630f1e72a1430ed","target":"record","created_at":"2026-05-17T23:59:48Z","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":"90c656265c32afcf794f443b3f2f80aa2e6c85e9d6eb6a920002e3e957a2a1b6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-22T10:19:22Z","title_canon_sha256":"34d22b7ce7947107710d47301df2689595ab3d8f48bb97bb220d15a3c3c9e0e3"},"schema_version":"1.0","source":{"id":"1811.10419","kind":"arxiv","version":1}},"canonical_sha256":"ae9875828b0475265314fb8ee7676d7f9b65b7525b874645adf98cc6387cd11a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae9875828b0475265314fb8ee7676d7f9b65b7525b874645adf98cc6387cd11a","first_computed_at":"2026-05-17T23:59:48.000928Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:48.000928Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"11RwqytZOFVfK2780WoTNxGXJSsVCfN21wmLjELq4NQCOQ95ADOfkKhTv2RdRUWirnNxH9S0S+3nYCfd5RI1BQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:48.001464Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.10419","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d7ec4664cc2793e59894b7083802d4eaf2ce5fe1b14fb0eee630f1e72a1430ed","sha256:7923ac6a8147c90e96da3a468eea67d3fca959d35ef5ef71d8e51777146eb9c0"],"state_sha256":"a017e2b92d1329c39f8eeacae9b189a2665b6e17323dce98692b86319a13915a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BOXbW+flV/qQjNWUuc7UueK6oSsFMQOPN4eg+kn0e1qxwQoN2dbiF063z8NByj61EV89M5iVFKxvsU64VIO9CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T15:27:32.692049Z","bundle_sha256":"baceb2392279ee29797ed3dbf3136b58da3f682e356bb16860683bb6f92bce22"}}