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pith:4QGQRAUK

pith:2026:4QGQRAUK6TP6VD75WYFB7A2EVE
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InfiltrNet: Dual-Branch CNN-Transformer Architecture for Brain Tumor Infiltration Risk Prediction

Shruti Kshirsagar, S M Asif Hossain

Dual-branch CNN-Transformer predicts three-zone glioma infiltration risk from multimodal MRI.

arxiv:2605.02230 v2 · 2026-05-04 · cs.CV · cs.LG

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\pithnumber{4QGQRAUK6TP6VD75WYFB7A2EVE}

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3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

InfiltrNet outperforms five established baselines on BraTS 2020 and BraTS 2025 for predicting three-zone infiltration risk maps from multimodal MRI.

C2weakest assumption

The distance-transform strategy on BraTS annotations produces labels that accurately reflect true biological infiltration risk rather than just geometric distance from the visible tumor.

C3one line summary

InfiltrNet uses a CNN-Transformer hybrid with distance-transform labels to generate infiltration risk maps from MRI and outperforms baselines on BraTS 2020 and 2025 datasets.

Formal links

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Receipt and verification
First computed 2026-06-23T02:12:49.520565Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

e40d08828af4dfea8ffdb60a1f8344a902744efc4cd673f53ccf248b77e2491d

Aliases

arxiv: 2605.02230 · arxiv_version: 2605.02230v2 · doi: 10.48550/arxiv.2605.02230 · pith_short_12: 4QGQRAUK6TP6 · pith_short_16: 4QGQRAUK6TP6VD75 · pith_short_8: 4QGQRAUK
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/4QGQRAUK6TP6VD75WYFB7A2EVE \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: e40d08828af4dfea8ffdb60a1f8344a902744efc4cd673f53ccf248b77e2491d
Canonical record JSON
{
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    "abstract_canon_sha256": "e9c98028427dc396fe5d0824eac174e8eafadf8030ec47d29b6977e199a5d40a",
    "cross_cats_sorted": [
      "cs.LG"
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-04T05:02:51Z",
    "title_canon_sha256": "ac01cd6eeeb5672ad0dbe17f32f85e5485176f9268fbd77dcc5f974550d9e8a8"
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