Paper Citation Record · LEDGER

Mitosis detection in domain shift scenarios: a Mamba-based approach

As of 19 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2508.21033.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.21033 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:38:55.962466Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy9
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eef8e4f8-39c4-4360-9fd8-6e320942eda8 · outbound

This paper cites Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A.

Mitosis detection in domain shift scenarios: a Mamba-based approach Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A

Reference 1

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T14:38:56.293396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation db5eb28e-c311-4121-9652-807b381670fa · outbound

This paper cites A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images.Medical Image Analysis, 84:102703, 2023.

Mitosis detection in domain shift scenarios: a Mamba-based approach A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images.Medical Image Analysis, 84:102703, 2023

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:58.459249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1c3f9117-9ad5-4317-b310-31549482c678 · outbound

This paper cites Mitosis detection, fast and slow: robust and efficient detection of mitotic figures.

Mitosis detection in domain shift scenarios: a Mamba-based approach Mitosis detection, fast and slow: robust and efficient detection of mitotic figures

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:58.114434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a67b3737-7bbe-4c4d-ae2c-cef9bec2d943 · outbound

This paper cites Bertram, Katharina Breininger, Dominik Hirling, Peter Horvath, Nikolas Stathonikos, and Mitko Veta.

Mitosis detection in domain shift scenarios: a Mamba-based approach Bertram, Katharina Breininger, Dominik Hirling, Peter Horvath, Nikolas Stathonikos, and Mitko Veta

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T14:38:54.863751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1ac805c-e923-4628-90ce-b259b66cb2cc · outbound

This paper cites Vmamba: Visual state space model.

Mitosis detection in domain shift scenarios: a Mamba-based approach Vmamba: Visual state space model

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:57.878820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7eba81eb-56f1-4c9e-8cba-912d80b0713f · outbound

This paper cites Mamba-sea: A mamba-based framework with global-to-local sequence augmentation for generalizable medical image segmentation.

Mitosis detection in domain shift scenarios: a Mamba-based approach Mamba-sea: A mamba-based framework with global-to-local sequence augmentation for generalizable medical image segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:57.660684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2b7c2a97-fe49-49ec-b945-4434d813cf66 · outbound

This paper cites Nuclick: a deep learning framework for interactive segmentation of microscopic images.

Mitosis detection in domain shift scenarios: a Mamba-based approach Nuclick: a deep learning framework for interactive segmentation of microscopic images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:57.436721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 259365d7-e050-4c97-9e7f-6c68f4e0574f · outbound

This paper cites VM-UNet: Vision Mamba UNet for Medical Image Segmentation.

Mitosis detection in domain shift scenarios: a Mamba-based approach VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T14:38:55.342986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c971554d-331b-469b-8350-07bf5cf678dd · outbound

This paper cites Imagenet: Constructing a large-scale image database.

Mitosis detection in domain shift scenarios: a Mamba-based approach Imagenet: Constructing a large-scale image database

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:57.236783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a650cfe-146a-4fa0-a1a1-1304a5089f66 · outbound

This paper cites Structure-preserving color normalization and sparse stain separation for histological im- ages.

Mitosis detection in domain shift scenarios: a Mamba-based approach Structure-preserving color normalization and sparse stain separation for histological im- ages

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:57.011713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f90d0930-b387-4510-9f17-017ec5f1245d · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

Mitosis detection in domain shift scenarios: a Mamba-based approach V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:56.764330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a3266880-3796-4a22-9360-9dea62b8ef08 · outbound

This paper cites Focal loss for dense object detection.

Mitosis detection in domain shift scenarios: a Mamba-based approach Focal loss for dense object detection

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T14:38:55.763890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cf060c0-2080-4d84-ad18-746e9f173ce4 · outbound

This paper cites Dono- van, Samir Jabari, Mitko Veta, Jonathan Ganz, Jonas Ammeling, Paul J.

Mitosis detection in domain shift scenarios: a Mamba-based approach Dono- van, Samir Jabari, Mitko Veta, Jonathan Ganz, Jonas Ammeling, Paul J

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T14:38:55.828103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42cce926-89d9-4ece-82db-51d3a3946b90 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Mitosis detection in domain shift scenarios: a Mamba-based approach U-net: Convolutional networks for biomedical image segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:38:56.532884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.