Keywords

1 Introduction

Optical imaging system is one of the most promising modalities that are emerging in recent years. Near-infrared optical imaging is a non-invasive method to analyse the tissue of the body in near-infrared range in the optical therapeutic window (650–1300 nm) associated with less absorption and enhanced scattering [1]. This non-invasive method is advancing the research and clinical applications from diagnosis of brain tissue in infants to functional imaging of cancer tissues at very early stages, even before it is visible with X-rays [2]. The optical radiation after entering the tissue medium, a fraction of it gets absorbed, scattered, backscattered or transmitted out [3, 4]. This complex interaction results in the backscattered radiation from multiple layers of tissues at various locations away from the beam entry point, as proved experimentally [4, 5] and theoretically [6,7,8]. The detectors close to the source receive signals from superficial layers, and those faraway receive signals from deeper layers. Thus by measuring the backscattered signals from different locations on the surface, emerging from various depths such as epithelium [9], breast and brain [10], their composition variations are determined.

Brain injury that happens during the perinatal period leads to death or severe impairment in several children who had premature birth [11]. The application of near-infrared imaging of the infant brain to monitor the cerebral oxygenation and haemodynamics was reported 30 years ago by Jobsis [12]. Optical tomography is a straightforward approach that involves acquiring multiple reflectance measurements from the surface of the head in rapid succession at small source-detector separations. The results obtained from a 32-channel optical imaging device which was developed by UCL, London, show variation in oxygen saturation at different regions in the brain of healthy preterm babies [13,14,15,16]. They come with reasonable spatial and temporal resolution, and have high repeatability [17].

In this study, a similar system consisting of an imaging patch with multiple sources and detectors around them was designed which gives information about two layers of tissues. This was provided by the detector with two source-detector separations. From the experiments, it is found that the system could be used to obtain images from shallow and deeper layers of tissues.

2 Methodology

The block diagram of the imaging set-up is shown in Fig. 1. It consists of light source and detectors, amplifiers to amplify the signals from the detectors, data acquisition set-up, data processing unit and display unit to display the resultant image.

Fig. 1
figure 1

Block diagram of the imaging set-up

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2.1 Light Source and Detector Module

The light source-detector module is called as the imaging patch consists of IR LED sources and photodiode detectors. The photodetectors are mounted in dual–octal geometrical shape around each LED source as shown in Fig. 2. Each source has 16 detectors arranged in two concentric circles which are each made up of 8 detectors. The detector used for designing patch is BPW34, and the source used is IR LED 940 nm. The distance between the centre of the LED source and the centre of the photodiode placed in the first circle is 7 mm, and the distance between the centre of the LED source and the centre of the photodiode placed in the second circle is 14 mm. The source-detector distance was determined by the physical size of the components.

Fig. 2
figure 2

The design of the source (centre)-detector arrangement

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2.2 Data Acquisition Unit

The amplifier unit of the set-up consists of a current-to-voltage converter to process the current signal from the photodiode detector. The voltage is amplified using an amplifier and filtered to remove noise and common mode signals. These signals are fed to the analogue input ports of data acquisition unit which has several parallel ports to read the signals from all the detectors. The signals are then fed to the computer for further processing by the data acquisition card.

2.3 Data Processing Unit

Once the data is read by the computer, it is processed using the code written in MATLAB software. Noise is removed, and the result is displayed in the form of 2D images. For each measurement, two images are obtained from the data processed from the inner circle of detectors and outer circle of detectors.

3 Data Acquisition and Processing

3.1 Tissue-Equivalent Phantom

Data is acquired from tissue-equivalent phantoms, and the imaging device is tested. For this purpose, phantoms were prepared using paraffin wax by melting it and poured in rectangular containers. They are embedded with two objects of size 5 mm × 1 mm × 1 mm at 7 and 14 mm at different locations in the phantom. These objects are placed to mimic any absorbing type of inhomogeneity. The prepared phantom is shown in Fig. 3. The designed imaging patch is placed on the rectangular flat phantom to perform the experiments.

Fig. 3
figure 3

Tissue-equivalent phantom made using paraffin wax with embedded objects

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3.2 Data Acquisition

Before performing the study, dark current readings from the photodiode detectors are taken by keeping the imaging patch on the surface of a black chart paper without source illumination. Three experiments were performed to study the test the device.

Experiment 1

This experiment was performed to analyse detection capability of the diodes. For that, the imaging patch was moved horizontally on the phantom over the position of the embedded object. The readings were taken in the darkness to avoid interference from the other light sources. The light signals received by the photodiodes were converted into current signals. These are converted into voltage signals using transimpedance amplifier and further amplified in the signal-conditioning unit. The acquired data was fed into the DAQ and given to the computer system and the data is stored digitally in the Excel sheets.

Experiment 2

This experiment was performed to analyse the performance of detectors when only one source is switched ON at a time. First the source S1 was switched ON and S2 was switched OFF, and the patch was kept on the phantom where no object is embedded. Then it was kept on the phantom such that the source S1 is directly on the area where the object is embedded. After this, the patch moved such that the position of the source S2 is directly on the area where the object is embedded. Data was acquired from all the detectors during the above three positions of the imaging patch. Then the experiment was repeated with source S2 in ON condition while the source S1 was switched OFF. Data was acquired by all the detectors from the three positions.

Experiment 3

This study was done to simulate an imaging patch with nine sources with its detectors. Such an arrangement can be used to image a large area such as neonatal head with all the sources ON. It was performed by using one source ON, and data was acquired by the detectors around it. The patch was placed at nine positions on the phantom around the areas where the object was embedded at 7 mm depth. The source S1 is switched ON, and data was acquired from each position. The experiment was repeated by placing the imaging patch over the area where the object is embedded at 14 mm depth. The signals received by all the detectors were acquired.

3.3 Data Processing

The light signals received by the photodiodes were converted into current signals. These are converted into voltage signals using transimpedance amplifier and further amplified in the signal-conditioning unit. The acquired data was fed into the DAQ and given to the computer system, and the data is stored digitally in the Excel sheets. Dark current measured for each detector was subtracted from the data from the respective diodes before further processing. MATLAB software was used for processing of the data so that the desired output is obtained.

4 Results and Discussion

The data obtained from the three experiments performed was processed, and results were obtained.

4.1 Results from Study 1

The data obtained from study 1 was processed only for two detectors. The signal from one of the detectors from inner circle and one from outer circle is chosen to plot the graph which is Diode 8 from inner circle (Fig. 4a) and Diode 9 from outer circle (Fig. 4b). The presence of the absorbing object in the phantom is clearly represented as a dip in the graphs at position 4. The peak intensity of the signal is more from the diode in the inner circle compared to that at the outer circle as it is far away from the source. Same results were obtained from the signals from all the detectors.

Fig. 4
figure 4

Plot of the signals obtained from two detectors around one source when it is moved over the phantom. a Signal from the diode in the inner circle and b signal from the diode at the outer circle

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4.2 Results from Study 2

Figure 5 shows the data obtained when source S1 is ON and S2 is OFF. These are displayed as images of size 6 × 6 after subtracting the dark current from the respective detectors. The left side of this image (3 × 3) is the response of the detectors around the illuminated source S1, and the right side of the image (3 × 3) is the response of the detectors around the source S2 which is not illuminated. The detectors around S1 show the received reflected signal which is strong, and those around S2 received weak signals due to source S1 which is far away from them. This is clearly seen in the images shown in Fig. 5(a) 1–3. The images (b) 4–5 are the background-subtracted ones. Background subtraction removes the noise and gives a smooth image.

Fig. 5
figure 5

Images obtained when a Source S1 is on (a) 1–5 from top-left corner; 1—background, 2—S1 on the embedded object, 3—S2 on the embedded object, 4—difference between 1 and 2 and 5—difference between 1 and 3, b source S2 is on, (b) 1–5 from top-left corner; 1—background, 2—S1 on the embedded object, 3—S2 on the embedded object, 4—difference between 1 and 2 and 5—difference between 1 and 3, (a) 1–5 from top-left corner; (b) 1–5 from top-left corner

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Images shown in Fig. 5(a) 4–5 are the difference between 1 and 2 and 1 and 3, respectively. Image 1 is the background. The results obtained when source S2 is ON while S2 is OFF are shown in Fig. 5b, where images (b) 1–3 are images of the data acquired by the detectors, and the images (b) 4–5 are the background-subtracted ones. The interference signals from both the sources are minimal in the present set-up.

4.3 Result from Study 3

Data was obtained from different locations on the phantom over the two areas where the objects are embedded. The data obtained are two 9 × 9 matrices from the outer and inner detectors from the area where the object is embedded at 7 mm depth. These are processed and displayed as images shown in Fig. 6. The images and their 3D plots are obtained by the inner (Fig. 6a) and the outer sets of detectors (Fig. 6b). The intensity differences in the images show the presence of the object. While both the detector sets show the presence of the object, the inner detectors show it clearly driving to a conclusion that the object is present at a depth close to 7 mm which is also the distance between the source and the inner circle of detectors.

Fig. 6
figure 6

Reconstructed images and their 3D plots obtained by the a inner and b outer detectors when the embedded object is at 7 mm depth with source S1 is ON

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Similarly, Fig. 7 shows the images and their 3D plots obtained by the inner Fig. 7a and the outer set of detectors Fig. 7b. These images were obtained from the area where the object is at 14 mm depth from the surface. While both the detector sets show the presence of the object, the outer detectors show it clearly, close to its actual size driving to a conclusion that the object is present at a depth close to 14 mm which is similar to the source-detector (outer circle) separation.

Fig. 7
figure 7

Reconstructed images and their 3D plots obtained by the a inner and b outer detectors when the embedded object is at 14 mm depth with source S1 is ON

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5 Conclusion

The 32 photodiodes and 2 LED sources arrangement proves the low cost and portability of the instrument system. As compared with the other devices, this design or instrument provides uniqueness to the system in the market and from the current researches on the different imaging techniques. The system could detect the embedded objects at different depths which are equal to the source-detector separation in the imaging patch. The image can be obtained without any harm to subject, and also the movement of the subject is not required. The further advancement in the designed system can be done by using dual-energy NIR laser source instead of LED source with the acquisition in the real time. By incorporating more sources, it can be used to image a large area such as functional analysis of neonatal brain.