J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume | Paper Citation Record

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This paper cites Cryo-electron microscopy of viruses.Na- ture, 308(5954):32–36, 1984.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Cryo-electron microscopy of viruses.Na- ture, 308(5954):32–36, 1984

Reference 1

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Observation a432afec-3766-48d3-8d14-dd64a081edae · outbound

This paper cites Adaptive multi-column deep neural networks with applica- tion to robust image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Adaptive multi-column deep neural networks with applica- tion to robust image denoising

Reference 2

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Observation 351a64c3-6391-4808-8d50-7fe7346c5665 · outbound

This paper cites Layer Normalization.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Layer Normalization

Reference 3

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This paper cites Noise2self: Blind denoising by self-supervision.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Noise2self: Blind denoising by self-supervision

Reference 4

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Observation d09bb572-4af0-4a13-aa84-ab65c3c670c3 · outbound

This paper cites Topaz-denoise: general deep denoising models for cryoem and cryoet.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Topaz-denoise: general deep denoising models for cryoem and cryoet

Reference 5

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This paper cites A non-local algorithm for image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume A non-local algorithm for image denoising

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.747397Z

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Observation 4ef4189e-ef5d-45f6-8aa9-c5472273a5e1 · outbound

This paper cites Content-aware image restoration for electron microscopy.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Content-aware image restoration for electron microscopy

Reference 7

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Observation 5025fef5-8cd4-45f0-8b22-5b01f355a9dc · outbound

This paper cites A resolution criterion for electron tomography based on cross-validation.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume A resolution criterion for electron tomography based on cross-validation

Reference 8

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Observation 131e891f-836c-4e61-a471-4a7d759d2ea6 · outbound

This paper cites Simple baselines for image restoration.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Simple baselines for image restoration

Reference 9

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Observation aa17c060-2236-42dc-83db-893538945c83 · outbound

This paper cites Rethinking coarse-to-fine approach in sin- gle image deblurring.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Rethinking coarse-to-fine approach in sin- gle image deblurring

Reference 10

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This paper cites Adam: A method for stochastic opti- mization.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Adam: A method for stochastic opti- mization

Reference 11

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This paper cites Denoising prior driven deep neural network for image restoration.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Denoising prior driven deep neural network for image restoration

Reference 12

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Observation 20c35347-f650-4efa-8cad-dad326a953a5 · outbound

This paper cites Noise reduc- tion in electron tomographic reconstructions using nonlin- ear anisotropic diffusion.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Noise reduc- tion in electron tomographic reconstructions using nonlin- ear anisotropic diffusion

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.595501Z

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This paper cites Three-dimensional tomographic reconstruction in high voltage electron microscopy.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Three-dimensional tomographic reconstruction in high voltage electron microscopy

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.573860Z

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This paper cites Spider and web: processing and visualization of images in 3d electron microscopy and related fields.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Spider and web: processing and visualization of images in 3d electron microscopy and related fields

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.545955Z

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Observation 76fe87f9-4f94-4302-a363-b31377a564b6 · outbound

This paper cites Improved training of wasserstein gans.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Improved training of wasserstein gans

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.522997Z

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Observation 56e3c180-2a0e-42b1-80ff-8ebc85be28b1 · outbound

This paper cites Deep residual learning for image recognition.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Deep residual learning for image recognition

Reference 17

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Observation 649e1531-56d2-445a-a7c3-7bc1284debcc · outbound

This paper cites Image-to-image translation with conditional adver- sarial networks.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Image-to-image translation with conditional adver- sarial networks

Reference 18

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Observation 66e3dbac-3c23-4dad-89a3-e31dfe505dd3 · outbound

This paper cites Natural image denoising with convolutional networks.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Natural image denoising with convolutional networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.473423Z

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Observation fcfd6d58-e7a0-41fe-9e9e-a79af7cf45a6 · outbound

This paper cites Puca: patch-unshuffle and channel attention for enhanced self-supervised image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Puca: patch-unshuffle and channel attention for enhanced self-supervised image denoising

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.439674Z

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Observation 22abbeea-afb8-4801-a71f-62b115a45fa2 · outbound

This paper cites Computer visualization of three-dimensional image data using imod.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Computer visualization of three-dimensional image data using imod

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.413339Z

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Observation 70cc671e-1272-4f99-9229-6c0b6c73a4bc · outbound

This paper cites Noise2void-learning denoising from single noisy images.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Noise2void-learning denoising from single noisy images

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.385427Z

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Observation 2eb76815-3e4a-4118-8c7d-3d4750f52e8d · outbound

This paper cites High-quality self-supervised deep image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume High-quality self-supervised deep image denoising

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.353235Z

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Observation eb2b2100-51c6-4c47-9144-9789e6c8495b · outbound

This paper cites Ap- bsn: Self-supervised denoising for real-world images via asymmetric pd and blind-spot network.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Ap- bsn: Self-supervised denoising for real-world images via asymmetric pd and blind-spot network

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.327847Z

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Observation a63b0c37-7970-433c-9156-f08165a32d61 · outbound

This paper cites Noise2Noise: Learning Image Restoration without Clean Data.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Noise2Noise: Learning Image Restoration without Clean Data

Reference 25

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Observation 34acdc4d-8c73-4815-8a58-c84904b4a30d · outbound

This paper cites Nonlocal transform-domain filter for volumetric data denoising and reconstruction.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Nonlocal transform-domain filter for volumetric data denoising and reconstruction

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.306982Z

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Observation 7559a69d-db48-4b10-9ce3-9f9fe4bc7fe1 · outbound

This paper cites Improving the quality of electron tomography image volumes using pre-reconstruction filter- ing.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Improving the quality of electron tomography image volumes using pre-reconstruction filter- ing

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.289798Z

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Observation b3922ca2-4d9e-4646-a34e-66fd73a7c922 · outbound

This paper cites Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections.Advances in neu- ral information processing systems, 29, 2016.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections.Advances in neu- ral information processing systems, 29, 2016

Reference 28

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Observation fa19d1d5-9612-4276-bcc4-5cf83f7e4c2a · outbound

This paper cites Simulating the cellular context in synthetic datasets for cryo-electron tomography.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Simulating the cellular context in synthetic datasets for cryo-electron tomography

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.252551Z

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Observation 7934fb18-82ca-488d-b53d-bd85ff6dd917 · outbound

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

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 30

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Observation 526a5b54-7015-40ac-8e62-f6912b01b643 · outbound

This paper cites Noisier2noise: Learning to denoise from unpaired noisy data.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Noisier2noise: Learning to denoise from unpaired noisy data

Reference 31

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Observation a55b8e19-0df1-4c3b-ae18-bd661299294a · outbound

This paper cites Stripe and ring artifact removal with combined wavelet—fourier filtering.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Stripe and ring artifact removal with combined wavelet—fourier filtering

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.198366Z

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This paper cites Fourier slice photography.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Fourier slice photography

Reference 33

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Observation fe39f356-f88b-42a5-95b1-4e276b70a9b3 · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Pytorch: An im- perative style, high-performance deep learning library

Reference 34

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Observation 3641ad3b-f263-40a5-99fd-879ce5fae8a2 · outbound

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

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume U- net: Convolutional networks for biomedical image segmen- tation

Reference 35

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Observation 073d55f5-c49d-4003-8914-fdac55f242bb · outbound

This paper cites Bilateral filtering for gray and color images.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Bilateral filtering for gray and color images

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T14:59:14.687651Z

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Observation cb0655b6-0595-4578-b92f-49fecc4bf340 · outbound

This paper cites The promise and the challenges of cryo-electron tomography.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume The promise and the challenges of cryo-electron tomography

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.103610Z

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Observation 7e7a1648-46f7-44f8-92f6-bead7a286644 · outbound

This paper cites Efficient automatic noise re- duction of electron tomographic reconstructions based on iterative median filtering.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Efficient automatic noise re- duction of electron tomographic reconstructions based on iterative median filtering

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.078990Z

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Observation 03c60949-7a65-4727-b419-f9e73f07b15d · outbound

This paper cites Unpaired learning of deep image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Unpaired learning of deep image denoising

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.044038Z

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Observation 37c5d005-1785-4f25-b5a3-8bac7f1d76e8 · outbound

This paper cites Image denois- ing and inpainting with deep neural networks.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Image denois- ing and inpainting with deep neural networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.021995Z

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Observation 971f56ff-e760-4012-bd51-ee76ca34fd05 · outbound

This paper cites Self-supervised noise modeling and sparsity guided electron tomography volumetric image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Self-supervised noise modeling and sparsity guided electron tomography volumetric image denoising

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:15.002465Z

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Observation d4aeb923-f81c-4799-9acb-4c773ce0cece · outbound

This paper cites Self-supervised cryo-electron tomography volumetric image restoration from single noisy volume with sparsity constraint.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Self-supervised cryo-electron tomography volumetric image restoration from single noisy volume with sparsity constraint

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:14.983354Z

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Observation dd287242-f95b-44d4-9c88-920519c1964f · outbound

This paper cites Dual adversarial network: Toward real-world noise removal and noise generation.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Dual adversarial network: Toward real-world noise removal and noise generation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:14.963152Z

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Observation 8c5dcd05-7816-4636-b4ad-c188b3173004 · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Restormer: Efficient transformer for high-resolution image restoration

Reference 44

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Observation 5ba94cb0-9c5b-434c-a4cd-f2f0eff62b67 · outbound

This paper cites Multi-stage progressive image restoration.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Multi-stage progressive image restoration

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:14.928867Z

Source-reported events for the cited work

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Observation cca7a6e8-e2d1-4eea-9b08-f3a620caa185 · outbound

This paper cites Mm-bsn: Self-supervised image denoising for real-world with multi-mask based on blind-spot network.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Mm-bsn: Self-supervised image denoising for real-world with multi-mask based on blind-spot network

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:14.906397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d8cf8d10-9ec7-458f-8be0-78144c7404f9 · outbound

This paper cites Unleashing the Power of Self-Supervised Image Denoising: A Comprehensive Review.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Unleashing the Power of Self-Supervised Image Denoising: A Comprehensive Review

Reference 47

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Observation 6c7d7a49-16c4-4306-8aef-970f0f85d103 · outbound

This paper cites Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:59:14.879939Z

Source-reported events for the cited work

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Observation 08ec55f3-f309-41b4-835c-d9fba9c794fd · outbound

This paper cites Ffdnet: Toward a fast and flexible solution for cnn-based image denoising.

J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume Ffdnet: Toward a fast and flexible solution for cnn-based image denoising

Reference 49

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