Journal: MethodsX

Article Title: An automated neural network-based stage-specific malaria detection software using dimension reduction: The malaria microscopy classifier

doi: 10.1016/j.mex.2023.102189

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Article Snippet: Resource availability: , Software: https://github.com/KatharinaPreissinger/Malaria_stage_classifier Documentation: https://malaria-stage-classifier.readthedocs.io/en/latest/index.html Data set: https://zenodo.org/record/6866337 Equipment: • Albumax, 25 mg/L Gentamycin • RPMI 1640 • VWR microscope slides (90° ground edges, nominal thickness 0.8 - 1.0 mm), • MFP-3D AFM (Asylum Research, Oxford Instruments), • OTESPA-R3 from Bruker with a rectangular shape, a tip radius of 7–10 nm, a spring constant of 26 N/m, operated at a frequency of 280 - 300 kHz with a drive amplitude of 250 - 300 mV • AFM acquisition software: Igor Pro 6.37 • Olympus IX81 inverted microscope • OMICRON (Rodgau-Dudenhofe, Germany) LaserHub (405 nm 120 mW CW diode, 488 nm 200 mW CW diode, 561 nm 156 mW CW diode, 642 nm 140 mW CW diode) • OMICRON Control centre software (v.3.3.19) • EM-CCD camera (Andor iXon DU-885KCSO-VP, Oxford instruments) • emission filter set (TRF89901-EM-ET-405/488/561/640, Chroma Technology, Bellows Falls, VT USA) • coverslips (nominal thickness 150 μm).

Techniques: Software, Microscopy, Inverted Microscopy