SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images | Paper Citation Record

Observation 49206889-11b4-44ff-9084-557de798ec1b · outbound

This paper cites Prostate158-an expert-annotated 3t mri dataset and algorithm for prostate cancer detection.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Prostate158-an expert-annotated 3t mri dataset and algorithm for prostate cancer detection

Reference 1

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Observation 78a9b35a-2ef6-46c4-9fe5-bafbcf271f4f · outbound

This paper cites Data from nsclc-radiomics-genomics.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Data from nsclc-radiomics-genomics

Reference 2

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Observation 97cd595b-6d53-4de4-9906-49f412c8662d · outbound

This paper cites Covid-19 lung ct scans.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Covid-19 lung ct scans

Reference 3

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Observation 9444cf39-8751-4f9d-b55f-9ed256c689d6 · outbound

This paper cites Data from lidc-idri.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Data from lidc-idri

Reference 4

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Observation a191d93e-0fa3-410e-bf78-7ea1d814a4c9 · outbound

This paper cites Spatial proteomics in three-dimensional intact specimens.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Spatial proteomics in three-dimensional intact specimens

Reference 5

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Observation 72e7662d-3c89-497e-b3c0-7f1d3596f11c · outbound

This paper cites Segmenting the Inferior Alveolar Canal in CBCTs Volumes: the ToothFairy Challenge.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Segmenting the Inferior Alveolar Canal in CBCTs Volumes: the ToothFairy Challenge

Reference 6

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Observation 7a072a06-d77f-400e-9344-a2a5753724c6 · outbound

This paper cites Automatic Segmentation and Alignment of Uterine Shapes from 3D Ultrasound Data.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Automatic Segmentation and Alignment of Uterine Shapes from 3D Ultrasound Data

Reference 7

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Observation 24942653-8c24-4a5c-8a47-b54ccc843192 · outbound

This paper cites Miccai challenge on circuit reconstruction from electron microscopy images.https://cremi.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Miccai challenge on circuit reconstruction from electron microscopy images.https://cremi

Reference 8

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Observation e96c50ee-3504-48c3-924a-2601697a1530 · outbound

This paper cites TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images TotalSegmentator MRI: Robust Sequence-independent Segmentation of Multiple Anatomic Structures in MRI

Reference 9

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Observation 889640b6-92ec-4627-b883-926c203aafd7 · outbound

This paper cites CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

Reference 10

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Observation c9e07bc5-896b-42f7-aa0a-cfc34a65dd63 · outbound

This paper cites LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification

Reference 11

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Observation 2c42969c-a113-4cfd-8ae8-ea4812cf26d3 · outbound

This paper cites Ultrasound segmentation analysis via distinct and completed anatomical borders.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Ultrasound segmentation analysis via distinct and completed anatomical borders

Reference 12

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Observation 9463cb2b-bbca-416c-a517-0a399ef2aaa9 · outbound

This paper cites A large-scale multicenter breast cancer dce-mri benchmark dataset with expert segmentations.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images A large-scale multicenter breast cancer dce-mri benchmark dataset with expert segmentations

Reference 13

Resolution: verified exact; doi, observed 2026-08-01T05:13:30.530940Z

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Observation 2256a7b3-4f72-4786-86c2-4ec1ad194f56 · outbound

This paper cites A whole-body fdg-pet/ct dataset with manually annotated tumor lesions.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images A whole-body fdg-pet/ct dataset with manually annotated tumor lesions

Reference 14

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Observation e722baf5-d8e5-48ad-a5cb-26c5f1154070 · outbound

This paper cites Spider-lumbar spine segmentation in mr images: a dataset and a public benchmark.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Spider-lumbar spine segmentation in mr images: a dataset and a public benchmark

Reference 15

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Observation c95f3f1d-2b55-454a-8f05-c39a529403d9 · outbound

This paper cites Deep learning enables automatic detection and segmentation of brain metastases on multisequence mri.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Deep learning enables automatic detection and segmentation of brain metastases on multisequence mri

Reference 16

Resolution: verified exact; doi, observed 2026-08-01T05:13:30.432848Z

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Observation b0e797c9-100b-46b1-a81f-f62f1d924841 · outbound

This paper cites Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge

Reference 17

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Observation 1d0bb1fc-f121-422a-846c-b4cb8a1a624a · outbound

This paper cites Towards unifying anatomy segmentation: Automated generation of a full-body ct dataset, in: 2024 IEEE International Conference on Image Processing (ICIP), pp.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Towards unifying anatomy segmentation: Automated generation of a full-body ct dataset, in: 2024 IEEE International Conference on Image Processing (ICIP), pp

Reference 18

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Observation acbb1109-857f-4934-9757-10c85fa8c297 · outbound

This paper cites 3d whole body preclinical micro-ct database of subcutaneous tumors in mice with annotations from 3 annotators.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images 3d whole body preclinical micro-ct database of subcutaneous tumors in mice with annotations from 3 annotators

Reference 19

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Observation be11c504-0692-4347-9fea-6c28a973a9f5 · outbound

This paper cites Tracked 3d ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Tracked 3d ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry

Reference 20

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Observation e7484615-c672-4b26-bab3-ff877216c344 · outbound

This paper cites Emidec: a database usable for the automatic evaluation of myocardial infarction from delayed-enhancement cardiac mri.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Emidec: a database usable for the automatic evaluation of myocardial infarction from delayed-enhancement cardiac mri

Reference 21

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Observation 0ce5e881-2156-4f92-8bc4-1ae55199c9a3 · outbound

This paper cites Deep learning for segmentation using an open large-scale dataset in 2d echocardiography.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Deep learning for segmentation using an open large-scale dataset in 2d echocardiography

Reference 22

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Observation 5853782a-3755-42ba-8f4a-54ab7d27435e · outbound

This paper cites Abdomenatlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Abdomenatlas: A large-scale, detailed-annotated, & multi-center dataset for efficient transfer learning and open algorithmic benchmarking

Reference 23

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Observation 0a6d371b-4802-4e9b-a830-6a7441afdc0c · outbound

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SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Unresolved cited work

Reference 24

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Observation a4e03285-bda7-4a5f-ae5b-1a443b78ec44 · outbound

This paper cites an unresolved cited work.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Unresolved cited work

Reference 25

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.996076Z

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Observation e5e27a4f-8dad-4b1f-b641-22d6ff891eb6 · outbound

This paper cites Sdr-former: A siamese dual-resolution transformer for liver lesion classification using 3d multi-phase imaging.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Sdr-former: A siamese dual-resolution transformer for liver lesion classification using 3d multi-phase imaging

Reference 26

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Observation 9b3cd3ef-c8e7-4975-ac45-710f29e29c5e · outbound

This paper cites Segrap2023: A benchmark of organs-at-risk and gross tumor volume segmentation for radiotherapy planning of nasopharyngeal carcinoma.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Segrap2023: A benchmark of organs-at-risk and gross tumor volume segmentation for radiotherapy planning of nasopharyngeal carcinoma

Reference 27

Resolution: malformed identifier; no resolver link, observed 2026-08-01T05:08:19.267964Z

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Observation c954eac5-2cb7-4413-9405-f268de70d236 · outbound

This paper cites Towards data-efficient learning: A benchmark for covid-19 ct lung and infection segmentation.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Towards data-efficient learning: A benchmark for covid-19 ct lung and infection segmentation

Reference 28

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Observation 9fc7375c-05b3-4958-84fb-193e6b258ebd · outbound

This paper cites Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Automatic Organ and Pan-cancer Segmentation in Abdomen CT: the FLARE 2023 Challenge

Reference 29

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Observation d41321f6-a6dd-4b8e-86c0-48cd19b66e0c · outbound

This paper cites Duke liver dataset: A publicly available liver mri dataset with liver segmentation masks and series labels.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Duke liver dataset: A publicly available liver mri dataset with liver segmentation masks and series labels

Reference 30

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Observation 92f7e622-e797-4d32-a4a4-c8946ae8b47d · outbound

This paper cites Open access series of imaging studies (oasis): cross-sectional mri data in young, middle aged, nondemented, and demented older adults.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Open access series of imaging studies (oasis): cross-sectional mri data in young, middle aged, nondemented, and demented older adults

Reference 31

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Observation 0220167c-d6ba-4a9e-85b4-d511fda00ad7 · outbound

This paper cites Deep learning segmentation of the right ventricle in cardiac mri: the m&ms challenge.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Deep learning segmentation of the right ventricle in cardiac mri: the m&ms challenge

Reference 32

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Observation 6f46bdb9-a3b5-4299-986f-c73b43b782f0 · outbound

This paper cites type b aortic dissection cta collection with true and false lumen expert annotations for the development of ai-based algorithms.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images type b aortic dissection cta collection with true and false lumen expert annotations for the development of ai-based algorithms

Reference 33

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.843927Z

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Observation 2b843e07-3f8f-4d58-8b39-98dfa36d28e1 · outbound

This paper cites Cervical cancer—tumor heterogeneity: Serial functional and molecular imaging across the radiation therapy course in advanced cervical cancer (version 1).

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Cervical cancer—tumor heterogeneity: Serial functional and molecular imaging across the radiation therapy course in advanced cervical cancer (version 1)

Reference 34

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.749235Z

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Observation dfe8aac8-8338-47c1-af1d-58eaf331deff · outbound

This paper cites Voxel-level segmentation of pathologically-proven adrenocortical carcinoma with ki-67 expression (adrenal-acc-ki67-seg)[data set].

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Voxel-level segmentation of pathologically-proven adrenocortical carcinoma with ki-67 expression (adrenal-acc-ki67-seg)[data set]

Reference 35

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.642718Z

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Observation 4ff91125-b964-4b97-9bc1-33fb4d1aea43 · outbound

This paper cites Multimodality annotated hepatocellular carcinoma data set including pre-and post-tace with imaging segmentation.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Multimodality annotated hepatocellular carcinoma data set including pre-and post-tace with imaging segmentation

Reference 36

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Observation 54d0996f-b1b6-4405-8358-57cd4bb3c5c0 · outbound

This paper cites Trusted: The paired 3d transabdominal ultrasound and ct human data for kidney segmentation and registration research.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Trusted: The paired 3d transabdominal ultrasound and ct human data for kidney segmentation and registration research

Reference 37

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Observation 847d368c-1b68-442c-899d-47cccd315f07 · outbound

This paper cites Hvsmr-2.0: A 3d cardiovascular mr dataset for whole-heart segmentation in congenital heart disease.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Hvsmr-2.0: A 3d cardiovascular mr dataset for whole-heart segmentation in congenital heart disease

Reference 38

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Observation b841d12e-a330-48be-bdc2-f1e2a2bae01b · outbound

This paper cites Han-seg: The head and neck organ-at-risk ct and mr segmentation dataset.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Han-seg: The head and neck organ-at-risk ct and mr segmentation dataset

Reference 39

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Observation 9c47933f-76d2-458a-9392-8abef1fe6029 · outbound

This paper cites an unresolved cited work.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Unresolved cited work

Reference 40

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.549471Z

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Observation 635c1b62-f6f4-4b76-a417-5edc4f274357 · outbound

This paper cites Calibration and uncertainty for multirater volume assessment in multiorgan segmentation (curvas) challenge results.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Calibration and uncertainty for multirater volume assessment in multiorgan segmentation (curvas) challenge results

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-01T05:08:21.054122Z

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Observation 095797e5-ee62-462d-b4a5-4dcabe5580bc · outbound

This paper cites A new 2.5 d representation for lymph node detection in ct.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images A new 2.5 d representation for lymph node detection in ct

Reference 42

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.424606Z

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Observation c26f8d31-7e1c-4aba-ac4a-40eae60ea39f · outbound

This paper cites Preoperative ct and survival data for patients undergoing resection of colorectal liver metastases.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Preoperative ct and survival data for patients undergoing resection of colorectal liver metastases

Reference 43

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.335830Z

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Observation 485abe00-316e-42d4-b93d-e4834a1b7d94 · outbound

This paper cites Thyroid ultrasound cine-clip.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Thyroid ultrasound cine-clip

Reference 44

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Observation e7f93990-1c6a-411a-931f-0dc5b33aebfa · outbound

This paper cites Aeropath: An airway segmentation benchmark dataset with challenging pathology and baseline method.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Aeropath: An airway segmentation benchmark dataset with challenging pathology and baseline method

Reference 45

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Observation b682d019-2640-47e1-9ce6-e27dbbc3e260 · outbound

This paper cites Generation of digital phantoms of cell nuclei and simulation of image formation in 3d image cytometry.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Generation of digital phantoms of cell nuclei and simulation of image formation in 3d image cytometry

Reference 46

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.122540Z

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Observation ae1c237e-6f66-4e63-b68e-c5b620b0fc87 · outbound

This paper cites an unresolved cited work.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Unresolved cited work

Reference 47

Resolution: verified exact; doi, observed 2026-08-01T05:13:29.009653Z

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Observation ad54cc98-77f8-4151-a216-0a92f12973dd · outbound

This paper cites SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

Reference 48

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Observation f6212327-637e-4424-9d19-cdf428862e21 · outbound

This paper cites Axonem dataset: 3d axon instance segmentation of brain cortical regions, in: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Axonem dataset: 3d axon instance segmentation of brain cortical regions, in: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer

Reference 49

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Observation fc00d431-8ec2-4200-93aa-1d21a71bce93 · outbound

This paper cites an unresolved cited work.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Unresolved cited work

Reference 50

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Observation 12e75aae-e147-484d-8782-5b6f6aebdc8d · outbound

This paper cites Resect: a clinical database of pre-operative mri and intra-operative ultrasound in low-grade glioma surgeries.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Resect: a clinical database of pre-operative mri and intra-operative ultrasound in low-grade glioma surgeries

Reference 51

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Observation 5a6341ba-83f4-40ea-bd8e-ae137fed3bfc · outbound

This paper cites Deeplesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Deeplesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning

Reference 52

Resolution: verified exact; doi, observed 2026-08-01T05:13:28.940561Z

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Observation c72e9f1f-fb13-4af7-bd7b-058191054c9a · outbound

This paper cites an unresolved cited work.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Unresolved cited work

Reference 53

Resolution: verified exact; doi, observed 2026-08-01T05:13:28.830230Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 078f1add-518d-4545-819f-3056cb893eaf · outbound

This paper cites Data from lung ct segmentation challenge (lctsc)(version 3)[data set].

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Data from lung ct segmentation challenge (lctsc)(version 3)[data set]

Reference 54

Resolution: malformed identifier; no resolver link, observed 2026-08-01T05:08:22.612737Z

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Observation 4c94069a-48e9-4fc5-a964-37b9ae5cae05 · outbound

This paper cites The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-01T05:08:22.728851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b88e5a30-f9a0-4b11-8221-1a73cb3e9fa6 · outbound

This paper cites Vivim: a video vision mamba for ultrasound video segmentation.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Vivim: a video vision mamba for ultrasound video segmentation

Reference 56

Resolution: malformed identifier; no resolver link, observed 2026-08-01T05:08:22.809739Z

Source-reported events for the cited work

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Observation a1827326-e073-4f6d-a36b-0ef01af039c0 · outbound

This paper cites Coffee-break lung ct collection with scan images reconstructed at multiple imaging parameters.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Coffee-break lung ct collection with scan images reconstructed at multiple imaging parameters

Reference 57

Resolution: verified exact; doi, observed 2026-08-01T05:13:28.637694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4ec2c2ab-fb55-48f1-a300-ef34356b6ff1 · outbound

This paper cites Nis3d: A completely annotated benchmark for dense 3d nuclei image segmentation.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Nis3d: A completely annotated benchmark for dense 3d nuclei image segmentation

Reference 58

Resolution: verified exact; doi, observed 2026-08-01T05:13:28.437479Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 06c37705-c416-4c97-8c5f-8a8024ec77ea · outbound

This paper cites Automatic segmentation of mitochondria and endolysosomes in volumetric electron microscopy data.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Automatic segmentation of mitochondria and endolysosomes in volumetric electron microscopy data

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-01T05:08:23.087448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84ac9bc2-db81-4721-9922-d1fe6f6d2032 · outbound

This paper cites an unresolved cited work.

SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Images Unresolved cited work

Reference 2025

Resolution: malformed identifier; no resolver link, observed 2026-08-01T05:08:22.088661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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