Published January 8, 2024 | Version v0.3.2
Dataset Open

Large-scale annotated dataset for cochlear hair cell detection and classification

Creators

  • 1. Eaton Peabody Laboratories, Mass Eye and Ear, Boston, MA, 02114 USA; Department of Otolaryngology, Head and Neck Surgery, Harvard Medical School, Boston, MA, 02114, USA; Speech and Hearing Biosciences and Technology graduate program, Harvard University, Cambridge, MA, USA
  • 2. Eaton Peabody Laboratories, Mass Eye and Ear, Boston, MA, 02114 USA; Department of Otolaryngology, Head and Neck Surgery, Harvard Medical School, Boston, MA, 02114, USA; Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA
  • 3. Eaton Peabody Laboratories, Mass Eye and Ear, Boston, MA, 02114 USA
  • 4. Eaton Peabody Laboratories, Mass Eye and Ear, Boston, MA, 02114 USA; Department of Otolaryngology, Head and Neck Surgery, Harvard Medical School, Boston, MA, 02114, USA
  • 5. Section on Sensory Cell Biology, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD 20814 USA
  • 6. Department of Otolaryngology, Head and Neck Surgery, Vienna General Hospital and Medical University of Vienna, Vienna, Austria
  • 7. Department of Otolaryngology, Washington University School of Medicine, St. Louis, MO, USA; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
  • 8. The Jackson Laboratory, Bar Harbor, ME, 04609, USA
  • 9. Department of Otolaryngology-Head and Neck Surgery, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
  • 10. ROR icon Massachusetts Eye and Ear Infirmary
  • 11. ROR icon Harvard Medical School
  • 12. The University of Mississippi Medical Center, Dept. of Otolaryngology - Head and Neck Surgery, Jackson, MS, USA
  • 13. Department of Otolaryngology-Head and Neck Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA
  • 14. Tina and Rick Caruso Department of Otolaryngology-Head and Neck Surgery, University of Southern California, Los Angeles, CA, 90033, USA; Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research, University of Southern California, Los Angeles, CA, 92037, USA
  • 15. ROR icon University of Sussex
  • 16. ROR icon University of Kentucky
  • 17. ROR icon National Institute on Deafness and Other Communication Disorders
  • 18. ROR icon University of Florida
  • 19. Department of Neurobiology, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA; Department of Surgery, Division of Otolaryngology, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA
  • 20. Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA; Department of Cell and Developmental Biology, University of California San Diego, La Jolla, CA 92093.
  • 21. Department of Otolaryngology, Stanford University School of Medicine, Stanford, CA 94305; Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305.
  • 22. The Jackson Laboratory, Bar Harbor, ME, 04609, USA; Department of Medicine, Tufts University, Boston, 02111, MA, USA; Graduate School of Biomedical Science and Engineering (GSBSE), University of Maine, Orono, 04469, ME, USA.
  • 23. Department of Otolaryngology-Head and Neck Surgery, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA; Department of Neurosciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
  • 24. Department of Otolaryngology, Washington University, 660 S. Euclid Avenue, Campus Box 8115, St. Louis, MO 63110, United States
  • 25. Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom

Description

Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5 - 15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitroototoxic drug application. The dataset includes over 107,000 hair cells which have been manually identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease. 

Associated code is provided here: https://github.com/indzhykulianlab/hcat-data

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