Taurine: a potential marker of apoptosis in gliomas von Opstad, K S, Bell, B A, Griffiths, J R, Howe, F A

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Linear discriminant analysis of brain tumour (1)H MR spectra: a comparison of classification using whole spectra versus metabolite quantification von Opstad, K S, Ladroue, C, Bell, B A, Griffiths, J R, Howe, F A

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Pattern recognition of MRSI data shows regions of glioma growth that agree with DTI markers of brain tumor infiltration von Wright, Alan J., Fellows, G., Byrnes, T. J., Opstad, K. S., McIntyre, D. J. O., Griffiths, J. R., Bell, B. A., Clark, C. A., Barrick, T. R., Howe, F. A.

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Classification of single-voxel 1H spectra of brain tumours using LCModel von Raschke, F., Fuster-Garcia, E., Opstad, K. S., Howe, F. A.

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Linear discriminant analysis of brain tumour 1H MR spectra: a comparison of classification using whole spectra versus metabolite quantification von Opstad, K. S., Ladroue, C., Bell, B. A., Griffiths, J. R., Howe, F. A.

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Detection of elevated glutathione in meningiomas by quantitative in vivo 1H MRS von Opstad, K.S., Provencher, S.W., Bell, B.A., Griffiths, J.R., Howe, F.A.

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Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy von Howe, F.A., Barton, S.J., Cudlip, S.A., Stubbs, M., Saunders, D.E., Murphy, M., Wilkins, P., Opstad, K.S., Doyle, V.L., McLean, M.A., Bell, B.A., Griffiths, J.R.

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Classification of single‐voxel 1 H spectra of brain tumours using LCModel von Raschke, F., Fuster‐Garcia, E., Opstad, K. S., Howe, F. A.

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Linear discriminant analysis of brain tumour 1 H MR spectra: a comparison of classification using whole spectra versus metabolite quantification von Opstad, K. S., Ladroue, C., Bell, B. A., Griffiths, J. R., Howe, F. A.

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super(1)H MR spectroscopy of brain tumours and masses von Howe, F A, Opstad, K S

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Differentiation of metastases from high-grade gliomas using short echo time super(1)H spectroscopy von Opstad, K S, Murphy, M M, Wilkins, PR, Bell, BA, Griffiths, J R, Howe, F A

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Soft thresholding schemes for multiple signal classification algorithm von Acuña, Sebastian, Opstad, Ida S., Godtliebsen, Fred, Ahluwalia, Balpreet Singh, Agarwal, Krishna

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Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning von Somani, Ayush, Ahmed Sekh, Arif, Opstad, Ida S, Birna Birgisdottir, Åsa, Myrmel, Truls, Singh Ahluwalia, Balpreet, Horsch, Alexander, Agarwal, Krishna, Prasad, Dilip K

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Fluorescence fluctuation-based super-resolution microscopy using multimodal waveguided illumination von Opstad, Ida S, Hansen, Daniel H, Acuña, Sebastian, Ströhl, Florian, Priyadarshi, Anish, Tinguely, Jean-Claude, Dullo, Firehun T, Dalmo, Roy A, Seternes, Tore, Ahluwalia, Balpreet S, Agarwal, Krishna

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Genetic Variation in ADAMTS13 is Related to VWF Levels, Atrial Fibrillation and Cerebral Ischemic Events von Warlo, Ellen M. K., Bratseth, Vibeke, Pettersen, Alf-Åge R., Holme, Pål Andre, Arnesen, Harald, Seljeflot, Ingebjørg, Opstad, Trine B.

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High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts von Godtliebsen, Gustav, Larsen, Kenneth Bowitz, Bhujabal, Zambarlal, Opstad, Ida S., Nager, Mireia, Punnakkal, Abhinanda R., Kalstad, Trine B., Olsen, Randi, Lund, Trine, Prasad, Dilip K., Agarwal, Krishna, Myrmel, Truls, Birgisdottir, Asa Birna

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Three-dimensional structured illumination microscopy data of mitochondria and lysosomes in cardiomyoblasts under normal and galactose-adapted conditions von Opstad, Ida S., Godtliebsen, Gustav, Ströhl, Florian, Myrmel, Truls, Ahluwalia, Balpreet Singh, Agarwal, Krishna, Birgisdottir, Åsa Birna

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Physics-based machine learning for subcellular segmentation in living cells von Sekh, Arif Ahmed, Opstad, Ida S., Godtliebsen, Gustav, Birgisdottir, Åsa Birna, Ahluwalia, Balpreet Singh, Agarwal, Krishna, Prasad, Dilip K.

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Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning von Jadhav, Suyog, Acuña, Sebastian, Opstad, Ida S, Singh Ahluwalia, Balpreet, Agarwal, Krishna, Prasad, Dilip K

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MusiJ: an ImageJ plugin for video nanoscopy von Acuña, Sebastian, Ströhl, Florian, Opstad, Ida S., Ahluwalia, Balpreet S., Agarwal, Krishna

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