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CBC and DBC Counter Using Image Processing — AI & Machine Learning project by YenkoDev

CBC and DBC Counter Using Image Processing

Software as a Service

No

Category

AI & Machine Learning

Clients

Mapua University

Techstack

PythonTensorFlowKerasOpenCVRaspberry PiPyQt4GSM Module

Purpose

Manual blood cell counting is slow and error-prone. This prototype automates complete and differential blood counts by analyzing microscope images of blood samples, giving laboratories faster and more consistent results for medical diagnostics.

Description

The system captures blood sample images through a Raspberry Pi camera and classifies red blood cells, white blood cells, and platelets with a convolutional neural network built on Keras and TensorFlow. OpenCV handles image preprocessing and cell segmentation, a PyQt desktop interface presents the counts, and a GSM module transmits results over SMS so the device can operate without an internet connection.

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