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Scanning acoustic microcopy (SAM) is widely used in biomedical and industrial applications in dermatology, ophthalmology, intravascular imaging, and small animal images, owing to SAM&rsquo, s ability to photograph small structures with a good spatial resolution. One of the most important devices of this system is the pulser/receiver (P/R) (PRN-300, Ohlabs Corporation, Nam-gu Busan, Republic of Korea), which generates pulses to trigger a high-frequency transducer. This article presents the design of a pulse generator to excite high-frequency transducers with four channels. The characteristics of the pulses, such as time and frequency, can be reconfigured by using a high-speed field programmable gate array (FPGA). The configuration software was developed for communicating with the P/R device via a USB connector for easy, feasible pulse selection and real-time pulse management. Besides that, during the design and implementation of the hardware, we optimized the damping resistor value to reduce the overshoot and undershoot part of the signal, ensuring the best effect on the transducer signal. The test results show that unipolar pulses worked with transducers with frequencies over 100 MHz. The SAM systems can work simultaneously with multiple transducers, and the resulting images have different resolutions of regions.

High-intensity focused ultrasound (HIFU) is a noninvasive therapy that uses focused ultrasound to treat a part of the tissue, high temperatures can damage tissues by heat. HIFU has many applications in the field of surgery and aesthetics and is used increasingly in everyday life. In this article, we discuss the mainboard design that controls the HIFU system with the ability to create a multistep sine wave compatible with many different applications. The signal used to trigger the transducer is a sinusoidal signal with a frequency adjustable from 0.1 to 3 MHz. In addition, the power supplied to the HIFU transducer is also controlled easily by the configuration parameters installed in the control circuit board. The proposed control and design method generates a voltage signal that doubles the supply voltage, thereby reducing the current on the MOSFET. The hardware design is optimized for a surface-mounted device-type MOSFET without the need for an external heat sink. In tests, we conducted a harmonious combination of two output signals to activate the same HIFU probe. The results showed that the energy transferred to the HIFU transducer increased by 1.5 times compared to a single channel. This means that the HIFU treatment time is reduced when using this method, with absolutely no changes in the system structure.

This paper presents the design of an Electrocardiogram (ECG) signal acquisition system based on 32-bit microprocessor platform. In hardware design, we present a complete design similar to the wearable devices used to monitor heart rates over the long term. The firmware is applied by an adaptive data compression method to increase storage space and reduces data transmission time between hardware devices and personal computer (PC). This adaptive algorithm is a combination of Joint Photographic Experts Group (JPEG) compression. The ECG signal was applied to the nearly-linear infinite impulse response (IIR) filter to eliminate noise from ECG signals. There are advantages of nearly-linear IIR filter over traditional IIR that the signal pass through filter is not distorted. Improvements in the JPEG compression algorithm make them suitable for one dimensional signals with a resolution greater than 8 bits and optimize the operation of the Huffman compression as well as the microcontroller unit (MCU) system with low processing speed. Placing the IIR filter at the end of the system promotes the ability to filter while reducing signal distortion after the decompression process. We tested the system with 8 records from the MIT/BIH cardiac arrhythmic database before and after we applied the compression algorithm to the firmware and software in the system that shows the effectiveness of these algorithms. The test results show that the system reached a maximum compression ratio of 8,8. The system deployed on the 32bit MCU (PIC32MZ2048), ECG analog front-end ADS1293 and operation time of ECG device up to 110 h (4.5 days).

The vast amount of data that is generated by today’s imaging technologies renders manual annotation and analysis infeasible. Novel workflows combining human and artificial intelligence are able to process terabyte-sized datasets. A new online neuron reconstruction service for light microscopy data achieves excellent accuracy meeting high scientific standards and reduces the required efforts to trace neurons.