Paper Citation Record · LEDGER

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.12208.

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

pith.paper-citation-record.v1
2506.12208 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:02:21.175140Z

measured 35 of 35 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

35 of 35 outbound references displayed

verified exact2
verified fuzzy18
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac69b819-9f90-4397-bb6e-1ab3c14042b8 · outbound

This paper cites Medical image segmentation re- view: The success of u-net.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Medical image segmentation re- view: The success of u-net

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.425622Z

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 376a252d-281a-47da-ad23-c18d19fb3c95 · outbound

This paper cites Dense dilated inception network for medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Dense dilated inception network for medical image segmentation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.419236Z

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 e85de237-2199-49f5-b1e0-05cba478dfac · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmenta- tion.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Swin-unet: Unet-like pure transformer for medical image segmenta- tion

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.412743Z

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 60eb2a8c-530f-4628-9e1a-0ec53e47d0f1 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.102978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44fe38f8-fbd9-471b-a921-f9ef86ab7a84 · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.105522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48dcf1c0-9eea-472d-8f7e-12af07f400d5 · outbound

This paper cites an unresolved cited work.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T01:02:21.406214Z

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 49577593-d6b2-44ba-b893-fa89fc26234f · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Imagenet: A large-scale hierarchical image database

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.111166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 119485f4-e1d6-4237-8b3e-3d00a79b7953 · outbound

This paper cites SA2-Net: Scale-aware Attention Network for Microscopic Image Segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation SA2-Net: Scale-aware Attention Network for Microscopic Image Segmentation

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-07T01:02:21.261497Z

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 08901387-1957-4280-b001-c47b3b043b1f · outbound

This paper cites Guided-attention and gated-aggregation network for medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Guided-attention and gated-aggregation network for medical image segmentation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.395251Z

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 2a78987e-79ec-4c7a-bf6f-39cdad3480f6 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.119040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68958754-8003-4e55-a8e3-d72297a52aef · outbound

This paper cites Segpc-2021: Seg- mentation of multiple myeloma plasma cells in microscopic images.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Segpc-2021: Seg- mentation of multiple myeloma plasma cells in microscopic images

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.386416Z

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 bf548100-4c23-47f6-bc5e-878b0bd91f22 · outbound

This paper cites Deep residual learning for image recognition.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Deep residual learning for image recognition

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.124127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e58199b-b903-4abe-97b1-f57ccffdebdf · outbound

This paper cites MISSFormer: An Effective Medical Image Segmentation Transformer.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation MISSFormer: An Effective Medical Image Segmentation Transformer

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.126176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0300fb3-193f-4925-a94b-cf67bf21df71 · outbound

This paper cites Multiresunet: Rethinking the u-net architecture for multimodal biomedical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Multiresunet: Rethinking the u-net architecture for multimodal biomedical image segmentation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.374103Z

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 c34fef3e-cc84-45df-9597-9e232f1c2332 · outbound

This paper cites Medical Image Segmentation Using Directional Window Attention.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Medical Image Segmentation Using Directional Window Attention

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T01:02:21.240579Z

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 c61e6299-19aa-4e2f-b835-9c490298b1ce · outbound

This paper cites Analyzing microbial pop- ulation heterogeneity—expanding the toolbox of microfluidic single-cell cultivations.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Analyzing microbial pop- ulation heterogeneity—expanding the toolbox of microfluidic single-cell cultivations

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.367791Z

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 b9926c6a-b214-4dcf-8e46-a8c4f9c0d32e · outbound

This paper cites Ds-transunet: Dual swin transformer u-net for medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Ds-transunet: Dual swin transformer u-net for medical image segmentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.361730Z

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 110994e1-7733-4be4-a89b-6a5f55255469 · outbound

This paper cites Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.137873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b15a6231-e0ad-4e43-8c74-8f1d933e3702 · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.140083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85793ecb-f31f-4e69-a055-2fff31572dd4 · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Attention U-Net: Learning Where to Look for the Pancreas

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.142179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f87d235-da9b-4444-861a-0c97ec6efd26 · outbound

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

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation U-net: Convolutional networks for biomedical image segmentation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.355133Z

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 1c4056c1-406c-4604-8f86-2587d191d71a · outbound

This paper cites Gland segmentation in colon histology images: The glas challenge contest.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Gland segmentation in colon histology images: The glas challenge contest

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.349013Z

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 e235e3dd-e86c-40b1-8ebf-8f004e0c9bd9 · outbound

This paper cites Going deeper with convolutions.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Going deeper with convolutions

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.148957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eabd6897-848d-4970-9b5e-21ae486e3d91 · outbound

This paper cites Rethinking the inception architecture for computer vision.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Rethinking the inception architecture for computer vision

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.151045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c58a7f19-054d-4e1b-9ebd-8009c76ab057 · outbound

This paper cites The fully convolutional transformer for medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation The fully convolutional transformer for medical image segmentation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.333827Z

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 501156da-f6c1-4f6f-839a-41fb071259d8 · outbound

This paper cites Med- ical transformer: Gated axial-attention for medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Med- ical transformer: Gated axial-attention for medical image segmentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.326918Z

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 bd1607eb-b75d-40bd-9fbd-5cd486861583 · outbound

This paper cites Uctransnet: rethinking the skip connections in u-net from a channel-wise perspective with transformer.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Uctransnet: rethinking the skip connections in u-net from a channel-wise perspective with transformer

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.320356Z

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 c14342c8-73a4-4e64-b08b-33ed99d0ec1c · outbound

This paper cites Narrowing the semantic gaps in u-net with learnable skip connections: The case of medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Narrowing the semantic gaps in u-net with learnable skip connections: The case of medical image segmentation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.313191Z

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 211f5677-af23-4f2a-95e2-7094abfe67e7 · outbound

This paper cites LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.161229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfc59011-cec5-4369-a1e0-8a48a7660187 · outbound

This paper cites U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.163533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78b9a48e-072f-4989-a023-437fe81a3d11 · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Pvt v2: Improved baselines with pyramid vision transformer

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:21.166116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19a8b059-8acb-417d-9542-99ed1af91840 · outbound

This paper cites SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.302698Z

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 a9ab5397-8f32-4a3c-bf57-80cf82d1487f · outbound

This paper cites An automatic nuclei image segmentation based on multi- scale split-attention u-net.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation An automatic nuclei image segmentation based on multi- scale split-attention u-net

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.296284Z

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 125f40e1-1f31-4644-9d58-f92b38d928c7 · outbound

This paper cites An effective cnn and transformer complementary network for medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation An effective cnn and transformer complementary network for medical image segmentation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.289268Z

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 3e3c68e3-dede-4270-a177-15974d82b27b · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmentation.

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation Unet++: A nested u-net architecture for medical image segmentation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T01:02:21.281977Z

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.