{"doi":"10.1364/oe.533880","title":"Hyperspectral acquisition with ScanImage at the single pixel level: application to time domain coherent Raman imaging","abstract":"We present a comprehensive strategy and its practical implementation using the commercial ScanImage software platform to perform hyperspectral point scanning microscopy when a fast time-dependent signal varies at each pixel level. In the proposed acquisition scheme, the scan along the X-axis is slowed down while the data acquisition is maintained at a high pace to enable the rapid acquisition of the time-dependent signal at each pixel level. The ScanImage generated raw 2D images have a very asymmetric aspect ratio between X and Y, the X axis encoding both for space and time acquisition. The results are X-axis macro-pixel where the associated time-dependent signal is sampled to provide hyperspectral information. We exemplified the proposed hyperspectral scheme in the context of time-domain coherent Raman imaging, where a pump pulse impulsively excites molecular vibrations that are subsequently probed by a time-delayed probe pulse. In this case, the time-dependent signal is a fast acousto-optics delay line that can scan a delay of 4.5ps in 25 μ s at each pixel level. With this acquisition scheme, we demonstrate ultra-fast hyperspectral vibrational imaging in the low frequency range [10 cm −1 , 150 cm −1 ] over a 500 μm field of view (64 x 64 pixels) in 130ms (∼ 7.5 frames/s). The proposed acquisition scheme can be readily extended to other applications requiring the acquisition of a fast-evolving signal at each pixel level.","journal":"Optics Express","year":2024,"id":481312,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9572,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1320971,"name":"Sisira Suresh","orcid":"0000-0003-1459-5933","position":1,"is_corresponding":false},{"id":1320972,"name":"Paulo Henrique Gonçalves Dias Diniz","orcid":"0000-0002-8652-5478","position":2,"is_corresponding":false},{"id":1321371,"name":"Chrysa Vourdaki","orcid":null,"position":3,"is_corresponding":false},{"id":1321372,"name":"Inés Martín","orcid":null,"position":4,"is_corresponding":false},{"id":948003,"name":"Siddarth Shivkumar","orcid":"0000-0001-9657-9755","position":5,"is_corresponding":false},{"id":422267,"name":"Randy A. Bartels","orcid":"0000-0003-0530-0435","position":6,"is_corresponding":false},{"id":1321373,"name":"Nicolas Forget","orcid":null,"position":7,"is_corresponding":false},{"id":488037,"name":"Hervé Rigneault","orcid":"0000-0001-6007-0631","position":8,"is_corresponding":false},{"id":1320970,"name":"Samuel Métais","orcid":"0009-0000-1584-2882","position":0,"is_corresponding":true}],"reference_count":21,"raw_metadata":null,"created_at":"2026-07-19T02:07:06.225103Z","pmid":"39573716","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}