Start/Lehrstuhl/Alumni/Laxmi Gupta

Lehrstuhl

Laxmi Gupta

Dr.-Ing.

Laxmi Gupta

wissenschaftliche Mitarbeiterin

Curriculum Vitae

Jul 2017 – Mai 2021
Wissenschaftliche Mitarbeiterin, Lehrstuhl für Bildgebung und Bildverarbeitung, RWTH Aachen, Aachen
Mar 2015 – Jun 2017 M.Sc. Biomedical Engineering, FH Aachen- University of Applied Sciences, Jülich
Feb 2012 –  Aug 2012 MATLAB Expert bei CETPA Infotech Pvt. Ltd., Indien
Aug 2007 – Jul 2011 B.Tech Biomedical Engineering, West Bengal University of Technology, Indien

Journal-Veröffentlichungen

  • 2022article

    Laxmi Gupta, Barbara Mara Klinkhammer, Claudia Seikrit, Nina Fan, Nassim Bouteldja, Philipp Gräbel, Michael Gadermayr, Peter Boor and Dorit Merhof

    Large-scale extraction of interpretable features provides new insights into kidney histopathology – a proof-of-concept study

    In: Journal of Pathology Informatics

  • 2019article

    Michael Gadermayr, Laxmi Gupta, Vitus Appel, Peter Boor, Barbara Mara Klinkhammer and Dorit Merhof

    Generative Adversarial Networks for Facilitating Stain-Independent Supervised & Unsupervised Segmentation: A Study on Kidney Histology

    In: IEEE Transactions on Medical Imaging

Konferenz-Veröffentlichungen

  • 2021inproceedings

    Michael Gadermayr, Maximilian Tschuchnig, Laxmi Gupta, Nils Krämer, Daniel Truhn, Dorit Merhof and Burkhard Gess

    An asymmetric cycle-consistency loss for dealing with many-to-one mappings in image translation: a study on thigh MR scans

    In: IEEE International Symposium on Biomedical Imaging (ISBI)

  • 2019inproceedings

    Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr

    GAN-Based Image Enrichment in Digital Pathology Boosts Segmentation Accuracy

    In: International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)

  • 2019inproceedings

    Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr

    Iterative learning to make the most of unlabeled and quickly obtained labeled data in histology

    In: 2nd International Conference on Medical Imaging with Deep Learning (MIDL)

  • 2019incollection

    Michael Gadermayr, Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor and Dorit Merhof

    Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations

    In: 2nd International Conference on Medical Imaging with Deep Learning (MIDL)

  • 2018inproceedings

    Laxmi Gupta, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof and Michael Gadermayr

    Stain Independent Segmentation of Whole Slide Images: A Case Study in Renal Histology

    In: IEEE International Symposium on Biomedical Imaging (ISBI)

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