{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:UXZTZACRD7QWOQQX4OJ4HU5DFR","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":"5474f094b16b82719eaeb6f6a45ef174e3f4374e53f01bc17e937e111da2dc7a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2019-08-02T12:20:59Z","title_canon_sha256":"ffc1491a155c6c3e6b0172cf266337a735222ae50c1ea84c2fb14baa2406b9fd"},"schema_version":"1.0","source":{"id":"1908.00822","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.00822","created_at":"2026-07-04T23:51:09Z"},{"alias_kind":"arxiv_version","alias_value":"1908.00822v1","created_at":"2026-07-04T23:51:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.00822","created_at":"2026-07-04T23:51:09Z"},{"alias_kind":"pith_short_12","alias_value":"UXZTZACRD7QW","created_at":"2026-07-04T23:51:09Z"},{"alias_kind":"pith_short_16","alias_value":"UXZTZACRD7QWOQQX","created_at":"2026-07-04T23:51:09Z"},{"alias_kind":"pith_short_8","alias_value":"UXZTZACR","created_at":"2026-07-04T23:51:09Z"}],"graph_snapshots":[{"event_id":"sha256:ab8a0e11c84eaf646a1ff091afcf35a12384d5ca66e54978ab6afc5d420829fe","target":"graph","created_at":"2026-07-04T23:51:09Z","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/1908.00822/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Window width (WW) and window level (WL) adjustments aid in visualizing anatomies with a suitable contrast. However, the presence of background noise in MR images biases the calculation of default WW/WL values since it necessitates a trade-off between enhancing contrast of foreground/anatomy of interest vs suppressing background/ outside the anatomy of interest. This paper proposes an intelligent algorithm to improve the automatic computation of WW/WL and provide better control for user defined windowing.This is achieved by first eliminating the background pixels using a Deep Neural network and","authors_text":"Deepthi Sundaran, Dheeraj Kulkarni, Jignesh Dholakia","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2019-08-02T12:20:59Z","title":"Optimal Windowing of MR Images using Deep Learning: An Enabler for Enhanced Visualization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.00822","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:d9777f96349deeb8048b060a5daa148fb641f67654651e33abd90c152213ef71","target":"record","created_at":"2026-07-04T23:51:09Z","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":"5474f094b16b82719eaeb6f6a45ef174e3f4374e53f01bc17e937e111da2dc7a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2019-08-02T12:20:59Z","title_canon_sha256":"ffc1491a155c6c3e6b0172cf266337a735222ae50c1ea84c2fb14baa2406b9fd"},"schema_version":"1.0","source":{"id":"1908.00822","kind":"arxiv","version":1}},"canonical_sha256":"a5f33c80511fe1674217e393c3d3a32c568a8310f0c8e9c1c0ddcc288460fc5a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5f33c80511fe1674217e393c3d3a32c568a8310f0c8e9c1c0ddcc288460fc5a","first_computed_at":"2026-07-04T23:51:09.834409Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:51:09.834409Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PSFWWJALv5JumW4zo2n8ONONg9az5bqJamBK3nNBgy+2Pz6/0fW8A0zpjtdYFhGe12tnXZ3lR957a91KoYF0Bg==","signature_status":"signed_v1","signed_at":"2026-07-04T23:51:09.834865Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.00822","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d9777f96349deeb8048b060a5daa148fb641f67654651e33abd90c152213ef71","sha256:ab8a0e11c84eaf646a1ff091afcf35a12384d5ca66e54978ab6afc5d420829fe"],"state_sha256":"e68a0c56f886daf17a97a0e74c2f940706b9cc6bc059657cf9f0f108b6b7e0e2"}