{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AP2GW3GABSL5L4GSXAADCO5AE7","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":"744b6afdc22c583dfebc7f0216b1d145ebfcee0b9e68f78e260928f4be0c647c","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-20T05:25:46Z","title_canon_sha256":"086884a7e5df46627695285b7dae5b2cdc349e724cb84751f2ada127f635084f"},"schema_version":"1.0","source":{"id":"2409.13229","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.13229","created_at":"2026-07-05T09:09:31Z"},{"alias_kind":"arxiv_version","alias_value":"2409.13229v1","created_at":"2026-07-05T09:09:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.13229","created_at":"2026-07-05T09:09:31Z"},{"alias_kind":"pith_short_12","alias_value":"AP2GW3GABSL5","created_at":"2026-07-05T09:09:31Z"},{"alias_kind":"pith_short_16","alias_value":"AP2GW3GABSL5L4GS","created_at":"2026-07-05T09:09:31Z"},{"alias_kind":"pith_short_8","alias_value":"AP2GW3GA","created_at":"2026-07-05T09:09:31Z"}],"graph_snapshots":[{"event_id":"sha256:3aa2cbdb3d8825f1d447e71178b5f597d4fb7b73e6320dac29fb23888a456d1c","target":"graph","created_at":"2026-07-05T09:09:31Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2409.13229/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Brain tumor segmentation plays a crucial role in computer-aided diagnosis. This study introduces a novel segmentation algorithm utilizing a modified nnU-Net architecture. Within the nnU-Net architecture's encoder section, we enhance conventional convolution layers by incorporating omni-dimensional dynamic convolution layers, resulting in improved feature representation. Simultaneously, we propose a multi-scale attention strategy that harnesses contemporary insights from various scales. Our model's efficacy is demonstrated on diverse datasets from the BraTS-2023 challenge. Integrating omni-dime","authors_text":"Aashray Gupta, Aayush Gupta, Sahaj K. Mistry, Sharath Chandra Guntuku, Sourav Saini, Sunny Rai, Ujjwal Baid, Vinit Jakhetiya","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-20T05:25:46Z","title":"Multiscale Encoder and Omni-Dimensional Dynamic Convolution Enrichment in nnU-Net for Brain Tumor Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.13229","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":"sha256:735175e6d98e6895f1e41a0a8bf2ea780f9542c13ebe8e985536403763e9742e","target":"record","created_at":"2026-07-05T09:09:31Z","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":"744b6afdc22c583dfebc7f0216b1d145ebfcee0b9e68f78e260928f4be0c647c","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-20T05:25:46Z","title_canon_sha256":"086884a7e5df46627695285b7dae5b2cdc349e724cb84751f2ada127f635084f"},"schema_version":"1.0","source":{"id":"2409.13229","kind":"arxiv","version":1}},"canonical_sha256":"03f46b6cc00c97d5f0d2b800313ba027e6c4b6e00497d792aae0a8767ab22d4b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"03f46b6cc00c97d5f0d2b800313ba027e6c4b6e00497d792aae0a8767ab22d4b","first_computed_at":"2026-07-05T09:09:31.437566Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:09:31.437566Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nlUXtYt0O7hR2x0/zGKngIBzV/WfKsfRLiLIXOQByCqKUGncmPT1lo0fXVr3gkS8RUyFAPdh18PnRLsKD961Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:09:31.438064Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.13229","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:735175e6d98e6895f1e41a0a8bf2ea780f9542c13ebe8e985536403763e9742e","sha256:3aa2cbdb3d8825f1d447e71178b5f597d4fb7b73e6320dac29fb23888a456d1c"],"state_sha256":"9cd9d51509b719ff23e7fbc8d90a4c9c8c5a1e2fafc9a2e10c5f274f941aaf80"}