{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:EL7DYGPV2JCJUJS6HAXKVYLADH","short_pith_number":"pith:EL7DYGPV","canonical_record":{"source":{"id":"1609.08508","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2016-09-27T15:57:30Z","cross_cats_sorted":[],"title_canon_sha256":"0ae9a9cc66d6f47a48a46428e84092b8dc9dec678d6afe62685b11125142f5e8","abstract_canon_sha256":"4e32ef4b7b3e479f11e8f780b85c31c899933b19bd773fe48d7dfb9163ee46ba"},"schema_version":"1.0"},"canonical_sha256":"22fe3c19f5d2449a265e382eaae16019ded8af7aab1adb706b70d4919df869c5","source":{"kind":"arxiv","id":"1609.08508","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.08508","created_at":"2026-05-18T01:03:45Z"},{"alias_kind":"arxiv_version","alias_value":"1609.08508v1","created_at":"2026-05-18T01:03:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.08508","created_at":"2026-05-18T01:03:45Z"},{"alias_kind":"pith_short_12","alias_value":"EL7DYGPV2JCJ","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"EL7DYGPV2JCJUJS6","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"EL7DYGPV","created_at":"2026-05-18T12:30:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:EL7DYGPV2JCJUJS6HAXKVYLADH","target":"record","payload":{"canonical_record":{"source":{"id":"1609.08508","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2016-09-27T15:57:30Z","cross_cats_sorted":[],"title_canon_sha256":"0ae9a9cc66d6f47a48a46428e84092b8dc9dec678d6afe62685b11125142f5e8","abstract_canon_sha256":"4e32ef4b7b3e479f11e8f780b85c31c899933b19bd773fe48d7dfb9163ee46ba"},"schema_version":"1.0"},"canonical_sha256":"22fe3c19f5d2449a265e382eaae16019ded8af7aab1adb706b70d4919df869c5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:03:45.751984Z","signature_b64":"BJjyAbjkisEPAEMGITxXmXvhxSPLlJ6THH1JERLWIhuu0Mb9UTLrQF4yS37azXIysoZkXcwk9VsfgYuVVxVjDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22fe3c19f5d2449a265e382eaae16019ded8af7aab1adb706b70d4919df869c5","last_reissued_at":"2026-05-18T01:03:45.751553Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:03:45.751553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1609.08508","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":"2026-05-18T01:03:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O7T55TlsWnrvPBLT6KAxWZd4AHVEeEiDd6aNisTp5hSH8yLhMZGmHCSlOnKeSdXJ6euMtGRdnLg1q4rmYYDuBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:22:51.662864Z"},"content_sha256":"e2dd80e211c126b9056ea7d69cf734cdbf50c0cb9b247d24a0dd7a0e111a9b33","schema_version":"1.0","event_id":"sha256:e2dd80e211c126b9056ea7d69cf734cdbf50c0cb9b247d24a0dd7a0e111a9b33"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:EL7DYGPV2JCJUJS6HAXKVYLADH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Low-Dose CT via Deep Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Ge Wang, Hu Chen, Jiliu Zhou, Ke Li, Peixi Liao, Weihua Zhang, Yi Zhang","submitted_at":"2016-09-27T15:57:30Z","abstract_excerpt":"In order to reduce the potential radiation risk, low-dose CT has attracted more and more attention. However, simply lowering the radiation dose will significantly degrade the imaging quality. In this paper, we propose a noise reduction method for low-dose CT via deep learning without accessing the original projection data. An architecture of deep convolutional neural network was considered to map the low-dose CT images into its corresponding normal-dose CT images patch by patch. Qualitative and quantitative evaluations demonstrate a state-the-art performance of the proposed method."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.08508","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":"2026-05-18T01:03:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8H8n5qI738+uIEAmDurt36yC8OVsPTEWRvVHetxc1TwLoeKXxaLKoiKWwdNdN1CpCXlw0HuxDGe1okE1yWq7DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T04:22:51.663212Z"},"content_sha256":"6abb117eda925ff451256640c9837e357eb55209f4df69f6059d262e1d996d35","schema_version":"1.0","event_id":"sha256:6abb117eda925ff451256640c9837e357eb55209f4df69f6059d262e1d996d35"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EL7DYGPV2JCJUJS6HAXKVYLADH/bundle.json","state_url":"https://pith.science/pith/EL7DYGPV2JCJUJS6HAXKVYLADH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EL7DYGPV2JCJUJS6HAXKVYLADH/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":"2026-05-27T04:22:51Z","links":{"resolver":"https://pith.science/pith/EL7DYGPV2JCJUJS6HAXKVYLADH","bundle":"https://pith.science/pith/EL7DYGPV2JCJUJS6HAXKVYLADH/bundle.json","state":"https://pith.science/pith/EL7DYGPV2JCJUJS6HAXKVYLADH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EL7DYGPV2JCJUJS6HAXKVYLADH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:EL7DYGPV2JCJUJS6HAXKVYLADH","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":"4e32ef4b7b3e479f11e8f780b85c31c899933b19bd773fe48d7dfb9163ee46ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2016-09-27T15:57:30Z","title_canon_sha256":"0ae9a9cc66d6f47a48a46428e84092b8dc9dec678d6afe62685b11125142f5e8"},"schema_version":"1.0","source":{"id":"1609.08508","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.08508","created_at":"2026-05-18T01:03:45Z"},{"alias_kind":"arxiv_version","alias_value":"1609.08508v1","created_at":"2026-05-18T01:03:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.08508","created_at":"2026-05-18T01:03:45Z"},{"alias_kind":"pith_short_12","alias_value":"EL7DYGPV2JCJ","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"EL7DYGPV2JCJUJS6","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"EL7DYGPV","created_at":"2026-05-18T12:30:12Z"}],"graph_snapshots":[{"event_id":"sha256:6abb117eda925ff451256640c9837e357eb55209f4df69f6059d262e1d996d35","target":"graph","created_at":"2026-05-18T01:03:45Z","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":"In order to reduce the potential radiation risk, low-dose CT has attracted more and more attention. However, simply lowering the radiation dose will significantly degrade the imaging quality. In this paper, we propose a noise reduction method for low-dose CT via deep learning without accessing the original projection data. An architecture of deep convolutional neural network was considered to map the low-dose CT images into its corresponding normal-dose CT images patch by patch. Qualitative and quantitative evaluations demonstrate a state-the-art performance of the proposed method.","authors_text":"Ge Wang, Hu Chen, Jiliu Zhou, Ke Li, Peixi Liao, Weihua Zhang, Yi Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2016-09-27T15:57:30Z","title":"Low-Dose CT via Deep Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.08508","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:e2dd80e211c126b9056ea7d69cf734cdbf50c0cb9b247d24a0dd7a0e111a9b33","target":"record","created_at":"2026-05-18T01:03:45Z","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":"4e32ef4b7b3e479f11e8f780b85c31c899933b19bd773fe48d7dfb9163ee46ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2016-09-27T15:57:30Z","title_canon_sha256":"0ae9a9cc66d6f47a48a46428e84092b8dc9dec678d6afe62685b11125142f5e8"},"schema_version":"1.0","source":{"id":"1609.08508","kind":"arxiv","version":1}},"canonical_sha256":"22fe3c19f5d2449a265e382eaae16019ded8af7aab1adb706b70d4919df869c5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22fe3c19f5d2449a265e382eaae16019ded8af7aab1adb706b70d4919df869c5","first_computed_at":"2026-05-18T01:03:45.751553Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:03:45.751553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BJjyAbjkisEPAEMGITxXmXvhxSPLlJ6THH1JERLWIhuu0Mb9UTLrQF4yS37azXIysoZkXcwk9VsfgYuVVxVjDg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:03:45.751984Z","signed_message":"canonical_sha256_bytes"},"source_id":"1609.08508","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e2dd80e211c126b9056ea7d69cf734cdbf50c0cb9b247d24a0dd7a0e111a9b33","sha256:6abb117eda925ff451256640c9837e357eb55209f4df69f6059d262e1d996d35"],"state_sha256":"d3b455127ee5758d6a313bfd15bf4fd4a09f104e4d6095654f724edde9f9f539"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1jfEfvbXIqqUEPAADJR4jWCms9ic+0OnfVliFFPmis29h6kviXnijdNeYUapvIHk7HPCfep2nWTcvURmrh5+CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T04:22:51.665353Z","bundle_sha256":"25428f9e8230d002292bd946c3abd57e002b8b4cc2e72a08350b5ad4236a9ff2"}}