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This shows the step by step of image processing and in this case, in detecting the sickle cells.

First, the image was input in the program (MATLAB). The image went through the first stage which was to pre-process the image right before denoising it. The image underwent segmentation as a step to group the image into several section or class label. The output image was then extracted based on the shape and features of the class label made with segmentation earlier. The last step was to analyse the final product of the image.

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In short, sickle cells is the red blood cells that shaped like a crescent moon due to abnormalities in the blood itself. Sickle cell disease occurs when a person inherits two abnormal copies of the haemoglobin gene, one from each parent. The abnormalities is that the oxygen-carrying protein haemoglobin found in the red blood cells. This leads to a rigid, sickle-like shape under circumstances. The sickness often begin around 5-6 months of age. A number of health problems may develop, such as attacks of pain ("sickle cell crisis"), anemia, swelling in the hands and feet, bacterial infections and stroke. Long-term pain may develop as people get older. The average life expectancy in the developed world is 40 to 60 years.

Random fact: People with sickle cells are resistant to the lethal disease Malaria.

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Image Processing and Semantic Segmentation

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Image Processing and Semantic Segmentation

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When using MATLAB, semantic segmentation is a possible route in processing an image to an image with divided section, this means that MATLAB will 'highlight and discard' the image taken of red blood cells to two sections, the blood cells itself and the background. This will render the process of image processing much easier and a much cleaner work space.

Based on the figure below, an image of a scenery at the beach was processed using network (semantic segmentation) and the output shows different sections made after processing; the ocean (blue), boat (red), sky (yellow) and land (purple).

Segmentation is essential for image analysis tasks. Image segmentation describes the process of associating each pixel of an image with a class label, (such as flower, person, road, sky, ocean or car).

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The reason MATLAB was chosen to detect the abnormal cells because the program MATLAB is built with a lot of functionality and thus can perform Image Segmentation. MATLAB is also widely available to people all around the world.