Paper Citation Record · LEDGER

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2412.05585.

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

pith.paper-citation-record.v1
2412.05585 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:38:40.784609Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

39 of 39 outbound references displayed

verified exact0
verified fuzzy36
unresolved3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba576cc3-1850-4446-9109-2cecf24aa583 · outbound

This paper cites an unresolved cited work.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-11T20:38:42.196223Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8aa81460-32a3-454b-8b6b-11c5ad69dcdd · outbound

This paper cites Computational and Mathematical Methods in Medicine 2020 (2020).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Computational and Mathematical Methods in Medicine 2020 (2020)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:42.100391Z

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Observation 1eb63384-b158-4480-b20a-ecf85665e2ad · outbound

This paper cites : A comparative study of breast cancer tumor classification by classical machine learning methods and deep learning method.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation : A comparative study of breast cancer tumor classification by classical machine learning methods and deep learning method

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.960683Z

Source-reported events for the cited work

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Observation 6a61b757-140d-48b6-a12e-e7b02d0566d1 · outbound

This paper cites Procedia Computer Science 171, 593–601 (2020).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Procedia Computer Science 171, 593–601 (2020)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.906631Z

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Observation 05c9576a-ea19-4649-aced-2156bbeb2b5c · outbound

This paper cites Computer Meth ods and Programs in Biomedicine 223, 106951 (2022).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Computer Meth ods and Programs in Biomedicine 223, 106951 (2022)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.897905Z

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Observation 75037e69-60fb-41fc-95a6-0e7d8db6e117 · outbound

This paper cites Ultrasonic imaging 38(3), 209– 224 (2016).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Ultrasonic imaging 38(3), 209– 224 (2016)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.888578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 60e41505-0300-419b-9805-27c3a3f1d191 · outbound

This paper cites PloS one 13(5), 0195816 (2018).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation PloS one 13(5), 0195816 (2018)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.879837Z

Source-reported events for the cited work

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Observation e681147f-be97-4626-aa9c-f90d9f93a6ad · outbound

This paper cites , Washington, K.N., Tran, T.D., Reiter, A., Bell, M.A.L.: Deep learning to obtain simultaneous image and segmentation outputs from a single input of raw ultrasound channel data.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation , Washington, K.N., Tran, T.D., Reiter, A., Bell, M.A.L.: Deep learning to obtain simultaneous image and segmentation outputs from a single input of raw ultrasound channel data

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.871221Z

Source-reported events for the cited work

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Observation 41dda81b-934a-4f82-b13c-b2ed8873b855 · outbound

This paper cites classification in computational pathology: application to mitosis analysis in breast cancer grading.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation classification in computational pathology: application to mitosis analysis in breast cancer grading

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.860838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8e368b53-53bd-4d08-b925-ed15d9d233a9 · outbound

This paper cites IEEE journal of biomedical and health informatics 24(4), 984–993 (2019) 15.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation IEEE journal of biomedical and health informatics 24(4), 984–993 (2019) 15

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.851633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9405289c-969a-4728-947b-2239498dc328 · outbound

This paper cites IEEE Transactions on Biome dical Engineering 68(3), 759–770 (2020).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation IEEE Transactions on Biome dical Engineering 68(3), 759–770 (2020)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.772234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 837e51ea-48cb-43d7-97ee-3a60e17b3639 · outbound

This paper cites Computers in biology and medicine 118, 103629 (2020).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Computers in biology and medicine 118, 103629 (2020)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.664771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3d42f236-794d-469f-84a4-5b4293c3a7df · outbound

This paper cites Ultrasound in Medicine & Biolog y 49(1), 31–44 (2023).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Ultrasound in Medicine & Biolog y 49(1), 31–44 (2023)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.656007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2895db4b-4ff8-4703-8940-0349205b208d · outbound

This paper cites Biomedical Signal Processing and Control 81, 104425 (2023).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Biomedical Signal Processing and Control 81, 104425 (2023)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.646983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cb047b8d-751c-400d-9112-622806e1fb85 · outbound

This paper cites Journal of King Saud University -Computer and Information Sciences 34(10), 10273–10292 (2022).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Journal of King Saud University -Computer and Information Sciences 34(10), 10273–10292 (2022)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.638117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3f0b47a9-9fc5-4a98-b90a-39cc5e2f06ae · outbound

This paper cites Expert Systems with Applications 213, 119024 (2023).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Expert Systems with Applications 213, 119024 (2023)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.629018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fde3d0cb-19d7-4228-a011-f4d286b8e06a · outbound

This paper cites IEEE journal of biomedical and health informatics 22(4), 1218–1226 (2017).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation IEEE journal of biomedical and health informatics 22(4), 1218–1226 (2017)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.619245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b2f7350c-6944-4df5-b68d-7ab26181f93c · outbound

This paper cites Data in brief 28, 104863 (2020).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Data in brief 28, 104863 (2020)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.610079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6b283a36-e82e-420c-ae72-1b38d52cdeab · outbound

This paper cites In: Journal of Physics: Conference Series, vol.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation In: Journal of Physics: Conference Series, vol

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.600963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation be951894-3692-41d0-bc5f-e711bba26a83 · outbound

This paper cites IEEE Transactions on Medical Imaging (2022).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation IEEE Transactions on Medical Imaging (2022)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.592039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 47e23c7e-baa7-4d6e-850b-9bbef5624475 · outbound

This paper cites In: Machine Learning in Medical Imaging: 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings 12, pp.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation In: Machine Learning in Medical Imaging: 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings 12, pp

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.583151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 89ca2663-aa98-4fa7-bcb4-3da47054c52c · outbound

This paper cites UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation

Reference 22

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Source-reported events for the cited work

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Observation d0433890-37da-4166-8af8-e133d13638cb · outbound

This paper cites In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.491617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ad27b382-06bc-417f-b367-099e91fa148c · outbound

This paper cites In: ICASSP 2020 -2020 IEEE International Conference on Acoustics, Speech and Signal Processing ( ICASSP), pp.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation In: ICASSP 2020 -2020 IEEE International Conference on Acoustics, Speech and Signal Processing ( ICASSP), pp

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.388080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 47e1feea-35a4-42e6-bcf9-6c92d2d95b60 · outbound

This paper cites In: European Conference on Computer Vision, pp.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation In: European Conference on Computer Vision, pp

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.298117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d4fd6411-1ffd-42f9-af5e-011a97ffcb8e · outbound

This paper cites In: 2019 IEEE International Symposium on Multimedia (ISM), pp.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation In: 2019 IEEE International Symposium on Multimedia (ISM), pp

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.285955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 94598da4-837e-4999-a296-45813558abcb · outbound

This paper cites Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T20:38:40.745908Z

Source-reported events for the cited work

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Observation 42bc1657-04e8-4abf-9789-bd8c59602db9 · outbound

This paper cites Computerized Medical Imaging and Graphics 70, 53–62 (2018).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Computerized Medical Imaging and Graphics 70, 53–62 (2018)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.277245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5120d627-6ab2-48b8-8e27-51784d5dfd53 · outbound

This paper cites IEEE Access 7, 105146 – 105158 (2019) 16.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation IEEE Access 7, 105146 – 105158 (2019) 16

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.266845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5df7c817-4904-4258-98a3-a7d3d928c049 · outbound

This paper cites Expert Systems with Applications 42(3), 990–1002 (2015).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Expert Systems with Applications 42(3), 990–1002 (2015)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.256225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 79de99ae-0213-48dd-934a-4e08fc84538a · outbound

This paper cites Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 9(2), 131–145 (2021).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 9(2), 131–145 (2021)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.201710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 11273d5e-d620-4fac-ab23-6961ea3111d9 · outbound

This paper cites Journal o f clinical medicine 9(3), 749 (2020).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Journal o f clinical medicine 9(3), 749 (2020)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.089913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f1195204-e9e3-41f1-84dc-c1c9a6ad61dc · outbound

This paper cites Procedia Computer Science 167, 878–889 (2020).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Procedia Computer Science 167, 878–889 (2020)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.080945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f42ab9af-30c7-41d0-a5d1-c2a6e5607503 · outbound

This paper cites EAI Endorsed Transactions on Scalable Information Systems 10(2), 4–4 (2023).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation EAI Endorsed Transactions on Scalable Information Systems 10(2), 4–4 (2023)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.070788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 816b8fef-49f4-4f19-8663-692f51fb9309 · outbound

This paper cites Ultrasonic imaging 44(1), 3–12 (2022).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Ultrasonic imaging 44(1), 3–12 (2022)

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.060236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 36103bd4-42e7-49c7-820f-b67983e0493e · outbound

This paper cites Biomedical Signal Processing and Control 75, 103553 (2022).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Biomedical Signal Processing and Control 75, 103553 (2022)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.049817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3ea199f9-5f42-42d1-a46f-b895330c1e62 · outbound

This paper cites Ultrasonics 121, 106682 (2022).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation Ultrasonics 121, 106682 (2022)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:41.039559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 085331e3-3dc5-47ed-8930-cd75f83ff94b · outbound

This paper cites In: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), pp.

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation In: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), pp

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:40.993649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4ab8ee25-938e-4ff3-ac0e-2e1442ae6dad · outbound

This paper cites IET Image Processing (2023).

UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation IET Image Processing (2023)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:38:40.891834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.