23 September 2021 | DigiBase invites you to attend a Spatial Biology webinar symposium to learn from experts in the field on how digital pathology, high-dimensional multiplexing, spatial and AI analytic tools, and spatial transcriptomic technologies are advancing tissue imaging and analysis.
Spatial Biology: Revolutionizing Tissue Imaging and Analysis Using Spatial profiling Read More »
Fill out the form below to request a chance to present your work using HALO or any of our other products or services.
Request to Present Read More »
Q1. As an intern, what projects were you assigned to work on? What skills did you acquire or improve while working on these projects?
A1. As an intern I was assigned to work on the Halo Link team. Before working on the Halo Link team I had no experience in Web Development which is the main skill I picked up in my time here so far. To be specific, before I started I did not know JavaScript and am now quite proficient at it along with learning an enterprise level framework and many other technologies that are needed to be a proficient developer.
An interview with Charles Habermehl, Software Engineer (Previous Intern) Read More »
Q1. As an intern, what projects were you assigned to work on? What skills did you acquire or improve while working on these projects?
A1. As an intern, I worked on the project to build quota-system where the customer can buy some quota whether it be quota for doing analysis, disk storage, etc. I also worked on building a loginAttempt feature where we can track important information such as customers’ ip address and which service they logged in from. The projects helped me in getting better at being able to design domain models, how middle-wares can work and how to hook up to GraphQL.
An interview with Anas Gauba, Software Engineer (Previous Intern) Read More »
Q1. As an intern, what projects were you assigned to work on? What skills did you acquire or improve while working on these projects?
A1. As an intern I worked on developing ASP.NET Core based infrastructure solutions utilizing https/web socket technology while incorporating native and db interactions.
Q2. What do you enjoy most about working at Indica Labs?
An interview with Dylan Balata, Software Engineer (Previous Intern) Read More »
An Interview with Adam Smith, Director of Life Science Applications, North America and Australasia
8 September 2021 | Digital pathology provides an advantage of automatizing many routine pathological tasks via computational algorithms and tools. The reporting of prostate cases is time-consuming due to a large number of slides per case. Moreover, tumor aggressivity grading (Gleason score) is well known for its subjective nature and high levels of interobserver variability. In this webinar, we will demonstrate a deep learning-based tool developed for the detection of prostate cancer in histological slides (prostate biopsies and prostatectomy specimens) and its histological grading (Gleason grading). We will present the results of the actual validation study showing high levels of accuracy in both tasks. We will discuss the practical aspects of the implementation of such tools in the diagnostic routine.
Automated Detection and Gleason Grading of Prostate Cancer in Digital Pathology Read More »
Albuquerque, NM, USA and Nottingham, UK, 1 July, 2021 – Following a formal tender process, Nottingham University Hospitals (NUH) NHS Trust today announced the selection of Indica Labs to aid in full digitisation of the pathology workflow. Indica Labs will deliver its leading digital pathology software, HALO AP®, fully integrated with existing hospital systems, alongside multiple Hamamatsu Nanozoomer scanners.
ALBUQUERQUE, NM and TEL AVIV, Israel – May 20, 2021 – Indica Labs, an industry leader in quantitative digital pathology & image management solutions, and Ibex Medical Analytics, a pioneer in artificial intelligence (AI) based cancer diagnostics, announced an agreement to integrate the Galen™ AI-based cancer diagnostics platform into the HALO AP® digital pathology workflow platform.
9 June 2021 | Deep learning can be applied to both clinical and research based digital pathology. Doing so can bring multiple advantages to both fields. In this talk, Dr. Peter Caie and Dr. Ines Nearchou we will discuss these advantages and describe a specific proof of principle that applies AI to the quantification of an important histopathological feature in colorectal cancer, desmoplastic reaction (DR).
