Medical Image Processing MATLAB Projects

Image-guided Precision Manipulation of Cells and Nanoparticles in Microfluidics

Manipulation of single cells and particles is important to biology and nanotechnology. Our electrokinetic (EK) tweezers manipulate objects in simple microfluidic devices using gentle fluid and electric forces under vision-based feedback control. In this dissertation, I detail a user-friendly implementation of EK tweezers that allows users to select, position, and assemble cells and nanoparticles.

This EK system was used to measure attachment forces between living breast cancer cells, trap single quantum dots with 45 nm accuracy, build nanophotonic circuits, and scan optical properties of nanowires. With a novel multi layer microfluidic device, EK was also used to guide single microspheres along complex 3D trajectories. The schemes, software, and methods developed here can be used in many settings to precisely manipulate most visible objects, assemble objects into useful structures, and improve the function of lab-on-a-chip microfluidic systems.

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White Blood Cell Segmentation in Microscopic Blood Images Using Digital Image Processing

Evaluation of blood smear is a commonly clinical test these days. Most of the time, the hematologists are interested on white blood cells (WBCs) only. Digital image processing techniques can help them in their analysis and diagnosis. For example, disease like acute leukemia is detected based on the amount and condition of the WBC.

The main objective of this paper is to segment the WBC to its two dominant elements: nucleus and cytoplasm. The segmentation is conducted using a proposed segmentation framework that consists of an integration of several digital image processing algorithms. Twenty microscopic blood images were tested, and the proposed framework managed to obtain 92% accuracy for nucleus segmentation and 78% for cytoplasm segmentation. The results indicate that the proposed framework is able to extract the nucleus and cytoplasm region in a WBC image sample.

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Microcontroller based Wireless Temperature and Heart Beat Read-out

we propose a Simple Wireless transmission System using common approach Sensor Platform called The wireless based Patient Sensor platform (WSP, Sensor Node) which has remote access capability.

The goals of the WSP are to establish: Standard sensor node (System on module), a common software. The proposed platform architecture (Sensor Node) offers flexibility, easy customization for different vital parameter collecting and sending.

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Embedded Internet for Pulse Oximeters

In recent years there has been many investigations into sleeping disorders. Many studies are carried out in specially equipped units in which a patient is monitored whilst sleeping. Measurements that are taken are in the form of ECG, EMG, EEG, nasal airflow, and abdominal movement.

Pulse oximetry data is also recorded during the night. Pulse oximetry is the measurement of pulse rate and oxygen saturation of blood. Along with other measurements pulse oximetry data is used in the diagnosis of sleeping disorders. Recent studies have shown that diagnosis of sleeping disorders is better suited to a location of familiarity rather than a hospital situation. Amongst others, this is one of the many reasons that remote monitoring of medical equipment, such as the pulse oximeter, is a forward step in sleep medicine.

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A Prototype for Blood Typing Based on Image Processing using MATLAB

This paper presents a new methodology for blood phenotyping based on the plate test and on image processing techniques to determine the occurrence of agglutination (between blood sample and reagent). A portable device for ABO-Rh blood typing and blood phenotying that automates all the analysis procedure, including mixture/centrifugation, reading and interpretation of results is presented. The system was tested with donor blood samples.

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Ultrasound Imaging: Signal Acquisition – New Advanced Processing for Biomedical and Industrial Applications using MATLAB

Use of ultrasound, namely in the biomedical diagnosis and industrial fields, pioneered in 1950s, is today particularly widespread. In the last decades, ultrasound imaging has benefited from advances in numerical technologies such as signal processing. On the other hand, the use of ultrasound imaging has increased the need for signal processing techniques. This paper presents a review and the up-to-date developments in ultrasound imaging techniques, including elementary principles, signal acquisition and processing, from one dimensional to multidimensional systems. This paper also deals with typical relevant applications.

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Detection of Cancer in Human Blood Sample based on Microscopic Images using MATLAB

At the moment, identification of blood disorders is through visual inspection of microscopic images of blood cells. From the identification of blood disorders, it can lead to classification of certain diseases related to blood. This paper describes a preliminary study of developing a detection of leukemia types using microscopic blood sample images. Analyzing through images is very important as from images, diseases can be detected and diagnosed at earlier stage. From there, further actions like controlling, monitoring and prevention of diseases can be done. Images are used as they are cheap and do not require expensive testing and lab equipments. The system will focus on white blood cells disease, leukemia. The system will use features in microscopic images and examine changes on texture, geometry, color and statistical analysis. Changes in these features will be used as a classifier input. A literature review has been done and Reinforcement Learning is proposed to classify types of leukemia. A little discussion about issues involved by researchers also has been prepared.

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