{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/rethinking-diffusion-model-for-multi-contrast","title":"Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution","arxiv_id":"2404.04785","date":"2024-04-07","proceeding":"CVPR 2024 1","authors":["Guangyuan Li","Chen Rao","Juncheng Mo","Zhanjie Zhang","Wei Xing","Lei Zhao"],"abstract":"Recently, diffusion models (DM) have been applied in magnetic resonance imaging (MRI) super-resolution (SR) reconstruction, exhibiting impressive performance, especially with regard to detailed reconstruction. However, the current DM-based SR reconstruction methods still face the following issues: (1) They require a large number of iterations to reconstruct the final image, which is inefficient and consumes a significant amount of computational resources. (2) The results reconstructed by these methods are often misaligned with the real high-resolution images, leading to remarkable distortion in the reconstructed MR images. To address the aforementioned issues, we propose an efficient diffusion model for multi-contrast MRI SR, named as DiffMSR. Specifically, we apply DM in a highly compact low-dimensional latent space to generate prior knowledge with high-frequency detail information. The highly compact latent space ensures that DM requires only a few simple iterations to produce accurate prior knowledge. In addition, we design the Prior-Guide Large Window Transformer (PLWformer) as the decoder for DM, which can extend the receptive field while fully utilizing the prior knowledge generated by DM to ensure that the reconstructed MR image remains undistorted. Extensive experiments on public and clinical datasets demonstrate that our DiffMSR outperforms state-of-the-art methods.","url_abs":"https://arxiv.org/abs/2404.04785v1","url_pdf":"https://arxiv.org/pdf/2404.04785v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"rethinking-diffusion-model-for-multi-contrast","repo_url":"https://github.com/guangyuankk/diffmsr","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"super-resolution","task_name":"Super-Resolution"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"diffusion","method_name":"Diffusion"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2404.04785","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.04785"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/guangyuankk/diffmsr","reach":{"status":"ok"}}],"summary":{"ran":5,"ran_draft_wrong":3,"ran_fixture":3},"by_repo_kind":{"official":{"samples":11,"ran":11,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":11,"samples":[{"code_sha256_prefix":"5d6168ba35db490b","entry":"FFT2D","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/models/DiffMSR_S1_model.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/models/DiffMSR_S1_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"5d6168ba35db490b"}},{"code_sha256_prefix":"f9c80fa2faac8e85","entry":"IFFT2D","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/models/DiffMSR_S1_model.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/models/DiffMSR_S1_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f9c80fa2faac8e85"}},{"code_sha256_prefix":"023a519d4baa7a71","entry":"data_consistency","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/models/DiffMSR_S1_model.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/models/DiffMSR_S1_model.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"023a519d4baa7a71"}},{"code_sha256_prefix":"8b0e794d4d8f9b13","entry":"default_conv","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/archs/common.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/archs/common.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"8b0e794d4d8f9b13"}},{"code_sha256_prefix":"ef9faf68f492a375","entry":"flow_warp","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/archs/arch_util.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/archs/arch_util.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"ef9faf68f492a375"}},{"code_sha256_prefix":"cd569444547de84f","entry":"get_position_from_periods","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/models/lr_scheduler.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/models/lr_scheduler.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"cd569444547de84f"}},{"code_sha256_prefix":"96ad5dc9ca239aec","entry":"make_layer","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/archs/arch_util.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/archs/arch_util.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"96ad5dc9ca239aec"}},{"code_sha256_prefix":"5a1d8458dc7077a6","entry":"resize_flow","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/archs/arch_util.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/archs/arch_util.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"5a1d8458dc7077a6"}},{"code_sha256_prefix":"82a15cc1e46f7e4d","entry":"to_3d","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/archs/CATL.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/archs/CATL.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"82a15cc1e46f7e4d"}},{"code_sha256_prefix":"b20f2a5df739a59e","entry":"to_4d","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/archs/CATL.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/archs/CATL.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"b20f2a5df739a59e"}},{"code_sha256_prefix":"60363d0620f5778d","entry":"window_partition","repo":"guangyuankk/diffmsr","repo_kind":"official","path":"DiffMSR_Main/archs/CATL.py","file_url":"https://github.com/guangyuankk/diffmsr/blob/HEAD/DiffMSR_Main/archs/CATL.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"60363d0620f5778d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}