Metraipolis › archive › dc_fe6bcff70f40

Acquisition Geometry-Assisted Whole-Group Localization of X-ray Fluorescence Maps in Optical Microscopy Images — arXiv:2608.18305

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.18305
License (as archived): CC0-1.0
Archived: 2026-10-18T14:06:10.258Z
SHA-256 of the archived text: b7b1278b3076d27d8c0d9ee50036ff3eb41ba5a83d0fd8ecfc91d289558612d8
Stable URL of this page: https://metraipolis.com/documento/dc_fe6bcff70f40

How to cite

Acquisition Geometry-Assisted Whole-Group Localization of X-ray Fluorescence Maps in Optical Microscopy Images — arXiv:2608.18305 — arXiv (en), https://arxiv.org/abs/2608.18305 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_fe6bcff70f40 (Metraipolis archive dc_fe6bcff70f40, sha256 b7b1278b3076d27d8c0d9ee50036ff3eb41ba5a83d0fd8ecfc91d289558612d8)

BibTeX

@misc{dcfe6bcff70f40,
  title = {Acquisition Geometry-Assisted Whole-Group Localization of X-ray Fluorescence Maps in Optical Microscopy Images — arXiv:2608.18305},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.18305},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_fe6bcff70f40; sha256 b7b1278b3076d27d8c0d9ee50036ff3eb41ba5a83d0fd8ecfc91d289558612d8},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.18305. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

X-ray fluorescence (XRF) microscopy maps elemental distributions, while optical microscopy can provide complementary morphological context. Localizing XRF fields of view (FOVs) in optical images is difficult because the two modalities differ in contrast mechanism and resolution. Most current workflows place each XRF tile independently, even when acquisition metadata already record the tiles' relative scan positions. This study formalizes XRF tile-group localization, in which one optical-frame placement is estimated for the whole group, constrained by acquisition geometry and quantified using group intersection-over-union (GroupIoU). In a controlled case study, independent localization failed with GroupIoU 0.000, whereas group localization achieved 0.931. Replacing the normalized cross-correlation (NCC) metric with mutual information (MI) gave nearly identical results, showing that the outcome is not specific to one local similarity metric. In another multiscale case study, using a coarse XRF survey scan to connect the fine-scale tile group to the optical image increased mean GroupIoU from 0.694 to 0.856. These case studies support using acquisition geometry as an explicit constraint when localizing related XRF tiles.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-08-20 in cs.CV).
Categorie arXiv: Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2608.18305 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-18T14:00:22.531Z dalla pagina https://arxiv.org/catchup/cs.CV/2026-08-20?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).