[Histonet] Next week – free webinar: “5 Common Mistakes when using Photoshop for Science”

[J. Sedgewick]

5 Common Mistakes when using Photoshop for Science: Tips, Tricks and a Case Study 

Sep 9, 2015 1:00 PM EDT at:

https://attendee.gotowebinar.com/register/2382965322253067778

Images are a vital component of scientific research for evaluation, data analysis, visualizing the impact of experimental parameters, and in medicine for assessing disease conditions. Regardless of the equipment price tag or level of automation, microscope systems generally fall short in providing images with consistent quality optimized for color, contrast and brightness. Adobe® Photoshop® or other image editing software is commonly used to correct for image insufficiencies, but consequences exist.

Join our speakers as they review the common mistakes encountered when using Photoshop for science, offer tips to achieve consistency and high quality in your imaging process, and share their personal experience on how to avoid these common mistakes altogether.

This webinar is co-sponsored by Imaging and Analysis, LLC and Datacolor Inc.

About the speakers:

Jerry Sedgewick (Imaging and Analysis, LLC), is an imaging consultant, an image forensic specialist, and a former core microscopy facility manager. As a recognized authority in applying Photoshop to edit scientific images, and through his books, articles and workshops, Mr. Sedgewick has helped hundreds of researchers use Photoshop to achieve their desired results.

Dr. Dawn M. Dawson received her M.D. from Eastern Virginia Medical School in 1989, followed by a residency and fellowship in Anatomic and Clinical Pathology at the Cleveland Clinic Foundation, receiving Board Certification in 1996. From 1998 until 2000, Dr. Dawson was a fellow in the Translational Research in Oncology Training Program. Currently, she is an Assistant Professor at Case Western Reserve University's Institute of Pathology and her responsibilities include immunohistochemistry activities. Her current research focuses on growth factor/receptors and cell signaling in carcinogenesis models.