wifi-densepose/vendor/ruvector/examples/rvf/examples/medical_imaging.rs

288 lines
11 KiB
Rust

//! Vertical Domain: Radiology Embedding Search with .rvvis
//!
//! Demonstrates RVF as a medical imaging retrieval substrate using the
//! DomainProfile::RvVision profile, triggered by the `.rvvis` file extension.
//!
//! Features:
//! - 150 image embedding vectors (512 dims) with radiology metadata
//! - Filtered search by modality and finding
//! - Combined filter: modality AND finding for targeted case retrieval
//! - Witness chain for audit trail (PROVENANCE + DATA_PROVENANCE)
//!
//! RVF segments used: VEC_SEG, MANIFEST_SEG, WITNESS_SEG
//!
//! Run: cargo run --example medical_imaging
use rvf_runtime::{
FilterExpr, MetadataEntry, MetadataValue, QueryOptions, RvfOptions, RvfStore, SearchResult,
};
use rvf_runtime::filter::FilterValue;
use rvf_runtime::options::DistanceMetric;
use rvf_crypto::{create_witness_chain, verify_witness_chain, shake256_256, WitnessEntry};
use tempfile::TempDir;
/// Simple LCG-based pseudo-random vector generator for deterministic results.
fn random_vector(dim: usize, seed: u64) -> Vec<f32> {
let mut v = Vec::with_capacity(dim);
let mut x = seed.wrapping_add(1);
for _ in 0..dim {
x = x.wrapping_mul(6364136223846793005).wrapping_add(1442695040888963407);
v.push(((x >> 33) as f32) / (u32::MAX as f32) - 0.5);
}
v
}
fn main() {
println!("=== Medical Imaging Retrieval (.rvvis) ===\n");
let dim = 512;
let num_images = 150;
let modalities = ["CT", "MRI", "XRay", "Ultrasound"];
let body_regions = ["chest", "abdomen", "head", "spine", "pelvis"];
let findings = ["normal", "fracture", "tumor", "pneumonia"];
// ====================================================================
// 1. Create store with .rvvis extension (DomainProfile::RvVision)
// ====================================================================
println!("--- 1. Create Radiology Store ---");
let tmp_dir = TempDir::new().expect("failed to create temp dir");
let store_path = tmp_dir.path().join("radiology.rvvis");
let options = RvfOptions {
dimension: dim as u16,
metric: DistanceMetric::L2,
..Default::default()
};
let mut store = RvfStore::create(&store_path, options).expect("failed to create store");
println!(" Store created with .rvvis extension (DomainProfile::RvVision)");
println!(" Dimensions: {} (image embedding space)", dim);
// ====================================================================
// 2. Insert 150 image embeddings with radiology metadata
// ====================================================================
println!("\n--- 2. Ingest Image Embeddings ---");
let vectors: Vec<Vec<f32>> = (0..num_images)
.map(|i| random_vector(dim, i as u64))
.collect();
let vec_refs: Vec<&[f32]> = vectors.iter().map(|v| v.as_slice()).collect();
let ids: Vec<u64> = (0..num_images as u64).collect();
// Metadata: modality (0), body_region (1), patient_age (2), finding (3)
let mut metadata = Vec::with_capacity(num_images * 4);
for i in 0..num_images {
let modality = modalities[i % modalities.len()];
let region = body_regions[i % body_regions.len()];
let age = (20 + (i * 3 + 7) % 61) as u64; // ages 20-80
let finding = findings[i % findings.len()];
metadata.push(MetadataEntry {
field_id: 0,
value: MetadataValue::String(modality.to_string()),
});
metadata.push(MetadataEntry {
field_id: 1,
value: MetadataValue::String(region.to_string()),
});
metadata.push(MetadataEntry {
field_id: 2,
value: MetadataValue::U64(age),
});
metadata.push(MetadataEntry {
field_id: 3,
value: MetadataValue::String(finding.to_string()),
});
}
let ingest = store
.ingest_batch(&vec_refs, &ids, Some(&metadata))
.expect("ingest failed");
println!(" Ingested {} image embeddings (rejected: {})", ingest.accepted, ingest.rejected);
// Print distribution
for m in &modalities {
let count = (0..num_images).filter(|i| modalities[i % modalities.len()] == *m).count();
println!(" {}: {} images", m, count);
}
// ====================================================================
// 3. Similar case search
// ====================================================================
println!("\n--- 3. Similar Case Search ---");
let query_vec = random_vector(dim, 42);
let k = 10;
let results = store
.query(&query_vec, k, &QueryOptions::default())
.expect("query failed");
println!(" Top-{} similar cases (unfiltered):", k);
print_imaging_results(&results, &modalities, &body_regions, &findings);
// ====================================================================
// 4. Filter by modality: MRI only
// ====================================================================
println!("\n--- 4. MRI Cases Only ---");
let filter_mri = FilterExpr::Eq(0, FilterValue::String("MRI".to_string()));
let opts_mri = QueryOptions {
filter: Some(filter_mri),
..Default::default()
};
let results_mri = store
.query(&query_vec, k, &opts_mri)
.expect("filtered query failed");
println!(" Top-{} MRI cases:", k);
print_imaging_results(&results_mri, &modalities, &body_regions, &findings);
for r in &results_mri {
let mod_idx = (r.id as usize) % modalities.len();
assert_eq!(modalities[mod_idx], "MRI");
}
println!(" All results verified: modality == MRI.");
// ====================================================================
// 5. Combined filter: CT AND tumor
// ====================================================================
println!("\n--- 5. CT Tumor Cases ---");
let filter_ct_tumor = FilterExpr::And(vec![
FilterExpr::Eq(0, FilterValue::String("CT".to_string())),
FilterExpr::Eq(3, FilterValue::String("tumor".to_string())),
]);
let opts_ct_tumor = QueryOptions {
filter: Some(filter_ct_tumor),
..Default::default()
};
let results_ct_tumor = store
.query(&query_vec, k, &opts_ct_tumor)
.expect("filtered query failed");
println!(" CT + tumor cases found: {}", results_ct_tumor.len());
if !results_ct_tumor.is_empty() {
print_imaging_results(&results_ct_tumor, &modalities, &body_regions, &findings);
}
let eligible_ct_tumor = (0..num_images)
.filter(|&i| {
modalities[i % modalities.len()] == "CT"
&& findings[i % findings.len()] == "tumor"
})
.count();
println!(
" Eligible in dataset: {} ({:.1}% selectivity)",
eligible_ct_tumor,
eligible_ct_tumor as f64 / num_images as f64 * 100.0
);
// ====================================================================
// 6. Filter by finding: pneumonia cases
// ====================================================================
println!("\n--- 6. Pneumonia Cases ---");
let filter_pneumonia = FilterExpr::Eq(3, FilterValue::String("pneumonia".to_string()));
let opts_pneumonia = QueryOptions {
filter: Some(filter_pneumonia),
..Default::default()
};
let results_pneumonia = store
.query(&query_vec, k, &opts_pneumonia)
.expect("filtered query failed");
println!(" Pneumonia cases found: {}", results_pneumonia.len());
if !results_pneumonia.is_empty() {
print_imaging_results(&results_pneumonia, &modalities, &body_regions, &findings);
}
// ====================================================================
// 7. Audit trail witness chain
// ====================================================================
println!("\n--- 7. Audit Trail (Witness Chain) ---");
let audit_steps = [
("image_acquisition", 0x01u8), // PROVENANCE
("dicom_parsing", 0x02), // COMPUTATION
("embedding_extraction", 0x02), // COMPUTATION
("case_indexing", 0x08), // DATA_PROVENANCE
("similarity_search", 0x02), // COMPUTATION
("report_generation", 0x08), // DATA_PROVENANCE
];
let entries: Vec<WitnessEntry> = audit_steps
.iter()
.enumerate()
.map(|(i, (step, wtype))| {
let action_data = format!("radiology:{}:{}", step, i);
WitnessEntry {
prev_hash: [0u8; 32],
action_hash: shake256_256(action_data.as_bytes()),
timestamp_ns: 1_700_000_000_000_000_000 + i as u64 * 30_000_000_000,
witness_type: *wtype,
}
})
.collect();
let chain_bytes = create_witness_chain(&entries);
let verified = verify_witness_chain(&chain_bytes).expect("chain verification failed");
println!(" Audit chain: {} entries, VALID", verified.len());
println!("\n Audit steps:");
for (i, (step, _)) in audit_steps.iter().enumerate() {
let wtype_name = match verified[i].witness_type {
0x01 => "PROV",
0x02 => "COMP",
0x08 => "DATA",
_ => "????",
};
println!(" [{}] {} -> {}", wtype_name, i, step);
}
// ====================================================================
// Summary
// ====================================================================
println!("\n=== Medical Imaging Summary ===\n");
println!(" Domain profile: RvVision (.rvvis)");
println!(" Images indexed: {}", num_images);
println!(" Embedding dims: {}", dim);
println!(" Unfiltered: {} results", results.len());
println!(" MRI only: {} results", results_mri.len());
println!(" CT + tumor: {} results", results_ct_tumor.len());
println!(" Pneumonia: {} results", results_pneumonia.len());
println!(" Audit trail: {} entries", audit_steps.len());
store.close().expect("failed to close store");
println!("\nDone.");
}
fn print_imaging_results(
results: &[SearchResult],
modalities: &[&str],
body_regions: &[&str],
findings: &[&str],
) {
println!(
" {:>6} {:>12} {:>10} {:>8} {:>4} {:>10}",
"ID", "Distance", "Modality", "Region", "Age", "Finding"
);
println!(
" {:->6} {:->12} {:->10} {:->8} {:->4} {:->10}",
"", "", "", "", "", ""
);
for r in results {
let idx = r.id as usize;
let modality = modalities[idx % modalities.len()];
let region = body_regions[idx % body_regions.len()];
let age = 20 + (idx * 3 + 7) % 61;
let finding = findings[idx % findings.len()];
println!(
" {:>6} {:>12.6} {:>10} {:>8} {:>4} {:>10}",
r.id, r.distance, modality, region, age, finding
);
}
}