The sophisticated HS Analysis Deep learning software is able to detect a plethora of sicknesses, one case is Colorectal Cancer. CC is a type of aggressive cancer that begins in the colon or the rectum. Specialists at HS Analysis are able to use advanced deep learning AI software to diagnose CC expertly along with its classes to aid clinics, institutions and health care facilities. The colon tissue can be roughly divided into three types:

  • healty tissue
  • adenoma = benign tissue
  • carcenoma = malignant cancer
Figure shows all kinds of tissue, green = healthy tissue, yellow = adenoma, red = carcinoma

The HS Analysis‘ touch:

One key technology of automatic interpretation of tissue samples in the HS Analysis software is the latest artificial intelligence. Deep learning evaluates a statistical predictive model for CC analysis by using algorithms to „learn“ how to recognize CC disease and gain access to variables that predict CC survival. Some examples include quantification, diameter measurements, and the separation of healthy and unhealthy tissue.

The HS Analysis software can help medical professionals diagnose disorders by examining high-resolution images of tissues and organs. And as the program generates data describing the patient’s current condition, it will assist doctors in selecting appropriate therapies, some examples of treatments will be discussed later in this blog.

HSA Scan software

The images below show the UI of HS Analysis KIT, in which the project name, tool bar and tabs, etc… can be seen.

Within the regions of interest, drawings with manual user annotations are made. After studying the annotations, the deep learning model applies them to several, larger regions of interest. The individual cell is annotated with respect to its type for example, the following images display that the healthy tissue is green, the adenoma are distinguished by yellow whereas the carcinoma in red. Their classes will be explained later on.

left tissue without annotations, right tissue with annotations (red=carcinoma)

For a better and more interactive viewing, you can move the slider from left to right as well as zoom in and out to see the true supreme tissue detection quality that our HS Analysis KIT can do on a small portion of a much larger whole slide picture of CC that was able to differentiate types of tissue and detected the exact diameter of each tissue. Below you can see the before and after CC healthy\adenoma/carcinoma annotation using the automated deep learning segmentation HS Analysis KIT model.

Furthermore, in terms of classes, we can see the many different classifications of the un-healthy cells that are detected by the HS Analysis software, just like the other annotations, these classes must first be annotated as well before they are trained with the deep learning model, there are 40+ CML classes that the HS Analysis KIT can learn from and it differentiates by its names and colors of the annotated structure, for example they range from the young\old Megakaryozyt to the very common and thin spiders web like NET.

(a) healthy tissue, (b) adenoma, (c) carcinoma

In terms of lab results, after the model is trained and ran the entire project, the HS Analysis software provides us with the information we need to understand the severity and condition in a sheet format, such as the name of the files, number of objects (structures) such as healthy and un-healthy tissue.

Or we can specify the deep learning analyzation of a single structure like adenoma.

Path finding algorithm

By utilizing the proprietary deep learning HS Analysis software and its lab result, Doctors can have an ease in mind knowing that these accurate results can assist in making decisions for patients that suffer from Colorectal Cancer or a research center that are seeking for a better insight into Colorectal Cancer.

State of the art Segmentation Architectures:

Left is a tissue cut from colon without annotations, right is the same tissue cut with annotations

Digitalization of histological slides and analysis with HSA KIT

HSA imports and works with 3dhistech and mirax files created by the Hamamatsu slide scanner. They are a perfect match for the HSA KIT.

If you don’t have a slide scanner and want to get one later, you can manually digitalize the slides on your microscope and create manual WSI using our inexpensive and affordable software (HSA SCAN M).

In this video, you can see manual scanning that converts a slide to a file with HSA SCAN software so that it can be trained and then automatically detected by a trained AI model using HSA KIT software.

If you want to automatically scan the slides, you can upgrade your microscope to an automated microscope station (HSA SCAN A). This converts your microscope into an automatic scanner for low-cost, high-quality performance in a short period of time.

HSA only requires the dimensions of your microscope and any specifications you wish to include, and we will send a stand and motor for your device that fits your microscope.

This will help you in:

  • Scanning faster
  • More accurate scanning
  • Saving time
  • Low budget
Automated microscope setup and the HSA Scan software

In above video, you can see an example of automatic scanner (HSA SCAN A). Do not hesitate to contact us for further information or ordering.

For more information or ordering :

Note: This website will be updated in future.