{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:AGJDXVUPCZUMWLFDHTNTE7TRRC","short_pith_number":"pith:AGJDXVUP","canonical_record":{"source":{"id":"1802.10426","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T14:18:36Z","cross_cats_sorted":[],"title_canon_sha256":"35a89aa9163292a9b29356c07634fdc97cedaed7d85bc439a33166fd171a81f9","abstract_canon_sha256":"5925980d21f04671bd8cdda4a26198fdb91ac94bee09e4da7a09b0fbcf2c5f07"},"schema_version":"1.0"},"canonical_sha256":"01923bd68f1668cb2ca33cdb327e7188bcf1a919db0f351920eb3263fbba8d71","source":{"kind":"arxiv","id":"1802.10426","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10426","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10426v1","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10426","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"pith_short_12","alias_value":"AGJDXVUPCZUM","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"AGJDXVUPCZUMWLFD","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"AGJDXVUP","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:AGJDXVUPCZUMWLFDHTNTE7TRRC","target":"record","payload":{"canonical_record":{"source":{"id":"1802.10426","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T14:18:36Z","cross_cats_sorted":[],"title_canon_sha256":"35a89aa9163292a9b29356c07634fdc97cedaed7d85bc439a33166fd171a81f9","abstract_canon_sha256":"5925980d21f04671bd8cdda4a26198fdb91ac94bee09e4da7a09b0fbcf2c5f07"},"schema_version":"1.0"},"canonical_sha256":"01923bd68f1668cb2ca33cdb327e7188bcf1a919db0f351920eb3263fbba8d71","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:22:17.166891Z","signature_b64":"iQcaIkRsFGtR0wnQNh7t8Drust/L2aVL+q4v6Nv/tnRccXMTgsG4fF8whuwDRC2nMxu2sGi2uANSttbMnkZJDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"01923bd68f1668cb2ca33cdb327e7188bcf1a919db0f351920eb3263fbba8d71","last_reissued_at":"2026-05-18T00:22:17.166344Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:22:17.166344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.10426","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":"2026-05-18T00:22:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P5fYLKm0T4zbSzovVtUT1tDbaV7Rz+aPbOv9th857/i2CTAo9CCSX1cDaEKByoAfMgG4I8iAKi/OZF4AJyU8Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T04:45:21.934258Z"},"content_sha256":"bace10928cac81bdc7dd68b8e3b157cbb78b9180bc4b4ba38286012d0dff8e67","schema_version":"1.0","event_id":"sha256:bace10928cac81bdc7dd68b8e3b157cbb78b9180bc4b4ba38286012d0dff8e67"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:AGJDXVUPCZUMWLFDHTNTE7TRRC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fine-grained wound tissue analysis using deep neural network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hamed Alizadeh Ghazijahani, Hossein Nejati, Kheng Hock Lee, Lian Leng Low, Milad Abdollahzadeh, Ngai-Man Cheung, Tooba Malekzadeh","submitted_at":"2018-02-28T14:18:36Z","abstract_excerpt":"Tissue assessment for chronic wounds is the basis of wound grading and selection of treatment approaches. While several image processing approaches have been proposed for automatic wound tissue analysis, there has been a shortcoming in these approaches for clinical practices. In particular, seemingly, all previous approaches have assumed only 3 tissue types in the chronic wounds, while these wounds commonly exhibit 7 distinct tissue types that presence of each one changes the treatment procedure. In this paper, for the first time, we investigate the classification of 7 wound issue types. We wo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10426","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":"2026-05-18T00:22:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FdCA63+gob4XS6dR68ElX5SJxCXFoG31stDwJOLSpQqnMkiE8z2RE4dCLtR2dNWWsEJAXemjMgNjSjO7z1PjBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T04:45:21.934829Z"},"content_sha256":"db4ea3892cc0b32fb3289b78aeed35dbb5f9dc0051f74c94239ea6e5555b9ccd","schema_version":"1.0","event_id":"sha256:db4ea3892cc0b32fb3289b78aeed35dbb5f9dc0051f74c94239ea6e5555b9ccd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AGJDXVUPCZUMWLFDHTNTE7TRRC/bundle.json","state_url":"https://pith.science/pith/AGJDXVUPCZUMWLFDHTNTE7TRRC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AGJDXVUPCZUMWLFDHTNTE7TRRC/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":"2026-06-03T04:45:21Z","links":{"resolver":"https://pith.science/pith/AGJDXVUPCZUMWLFDHTNTE7TRRC","bundle":"https://pith.science/pith/AGJDXVUPCZUMWLFDHTNTE7TRRC/bundle.json","state":"https://pith.science/pith/AGJDXVUPCZUMWLFDHTNTE7TRRC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AGJDXVUPCZUMWLFDHTNTE7TRRC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:AGJDXVUPCZUMWLFDHTNTE7TRRC","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":"5925980d21f04671bd8cdda4a26198fdb91ac94bee09e4da7a09b0fbcf2c5f07","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T14:18:36Z","title_canon_sha256":"35a89aa9163292a9b29356c07634fdc97cedaed7d85bc439a33166fd171a81f9"},"schema_version":"1.0","source":{"id":"1802.10426","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10426","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10426v1","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10426","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"pith_short_12","alias_value":"AGJDXVUPCZUM","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"AGJDXVUPCZUMWLFD","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"AGJDXVUP","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:db4ea3892cc0b32fb3289b78aeed35dbb5f9dc0051f74c94239ea6e5555b9ccd","target":"graph","created_at":"2026-05-18T00:22:17Z","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":"Tissue assessment for chronic wounds is the basis of wound grading and selection of treatment approaches. While several image processing approaches have been proposed for automatic wound tissue analysis, there has been a shortcoming in these approaches for clinical practices. In particular, seemingly, all previous approaches have assumed only 3 tissue types in the chronic wounds, while these wounds commonly exhibit 7 distinct tissue types that presence of each one changes the treatment procedure. In this paper, for the first time, we investigate the classification of 7 wound issue types. We wo","authors_text":"Hamed Alizadeh Ghazijahani, Hossein Nejati, Kheng Hock Lee, Lian Leng Low, Milad Abdollahzadeh, Ngai-Man Cheung, Tooba Malekzadeh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T14:18:36Z","title":"Fine-grained wound tissue analysis using deep neural network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10426","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:bace10928cac81bdc7dd68b8e3b157cbb78b9180bc4b4ba38286012d0dff8e67","target":"record","created_at":"2026-05-18T00:22:17Z","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":"5925980d21f04671bd8cdda4a26198fdb91ac94bee09e4da7a09b0fbcf2c5f07","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T14:18:36Z","title_canon_sha256":"35a89aa9163292a9b29356c07634fdc97cedaed7d85bc439a33166fd171a81f9"},"schema_version":"1.0","source":{"id":"1802.10426","kind":"arxiv","version":1}},"canonical_sha256":"01923bd68f1668cb2ca33cdb327e7188bcf1a919db0f351920eb3263fbba8d71","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"01923bd68f1668cb2ca33cdb327e7188bcf1a919db0f351920eb3263fbba8d71","first_computed_at":"2026-05-18T00:22:17.166344Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:22:17.166344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iQcaIkRsFGtR0wnQNh7t8Drust/L2aVL+q4v6Nv/tnRccXMTgsG4fF8whuwDRC2nMxu2sGi2uANSttbMnkZJDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:22:17.166891Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.10426","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bace10928cac81bdc7dd68b8e3b157cbb78b9180bc4b4ba38286012d0dff8e67","sha256:db4ea3892cc0b32fb3289b78aeed35dbb5f9dc0051f74c94239ea6e5555b9ccd"],"state_sha256":"062883a74e33aad78ee75678913ea84f92e7d7a128f187a93242c7c3569750c2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6vPVydKDmhRwiSKFTe4gpIwQWijqJU2fsp5RdJIjd1IWSTopj+8B0pVHN96GkqoUQdTfYNP//UgC8A3QjaDXBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T04:45:21.937592Z","bundle_sha256":"4faba30462f83b86301e27186d985fcb34a5f751845f982715f6535cdc54c514"}}