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Thermal ablation modalities, for example radiofrequency ablation (RFA) and microwave ablation, are intended to prompt controlled tumour removal by raising tissue temperature. However, monitoring the size of the resulting tissue damage during the thermal removal procedures is a challenging task. The objective of this study was to evaluate the observation of RFA on an ex vivo liver sample with both a commercial and a low-cost system to distinguish between the normal and the ablated regions as well as the thermally affected regions. RFA trials were conducted on five different ex vivo normal bovine samples and monitored initially by a custom hyperspectral (HS) camera to measure the diffuse reflectance (Rd) utilising a polychromatic light source (tungsten halogen lamp) within the spectral range 348–950 nm. Next, the light source was replaced with monochromatic LEDs (415, 565 and 660 nm) and a commercial charge-coupled device (CCD) camera was used instead of the HS camera. The system algorithm comprises image enhancement (normalisation and moving average filter) and image segmentation with K-means clustering, combining spectral and spatial information to assess the variable responses to polychromatic light and monochromatic LEDs to highlight the differences in the Rd properties of thermally affected/normal tissue regions. The measured spectral signatures of the various regions, besides the calculation of the standard deviations (δ) between the generated six groups, guided us to select three optimal wavelengths (420, 540 and 660 nm) to discriminate between these various regions. Next, we selected six spectral images to apply the image processing to (at 450, 500, 550, 600, 650 and 700 nm). We noticed that the optimum image is the superimposed spectral images at 550, 600, 650 and 700 nm, which are capable of discriminating between the various regions. Later, we measured Rd with the CCD camera and commercially available monochromatic LED light sources at 415, 565 and 660 nm. Compared to the HS camera results, this system was more capable of identifying the ablated and the thermally affected regions of surface RFA than the side-penetration RFA of the investigated ex vivo liver samples. However, we succeeded in developing a low-cost system that provides satisfactory information to highlight the ablated and thermally affected region to improve the outcome of surgical tumour ablation with much shorter time for image capture and processing compared to the HS system.

Breast malignancy is a critical problem that severely affects women’s health globally with a high-frequency rate, necessitating fast, effective, and early diagnostic methods. The present study aims to measure the breast tissue’s optical properties by capturing the spectral signatures from malignant and normal breast tissue for therapeutic and diagnostic applications. The optical imaging system incorporates a hyperspectral (HS) camera to capture the spectral signatures for both the malignant and normal breast tissues within 400 ~ 1000 nm. The system was subdivided into two exploratory (reflection/transmission) to measure the tissue’s diffuse reflectance (Rd) and light transmission (Tr), respectively. The study involved 30 breast tissue (normal/tumor) samples from 30 females in the age range of 46 ~ 72 years, who were optically inspected in the visible and near-infrared (VIS-NIR) spectra. Then, the inverse adding doubling (IAD) method for breast tissue characterization and descriptive analysis (T-test) was exploited to verify the significant difference between the various types of breast tissues and select the optimum wavelength. Finally, comparing the study outcome with the histopathological examination to evaluate the system’s effectiveness by calculation (sensitivity, specificity, and accuracy). The average outcome values demonstrated that the optimal spectral bands distinguishing between the normal and the tumor tissues regarding the reflectance approach were 600 ~ 680 nm and 750 ~ 960 nm at the VIS and NIR spectrum, respectively. Then, for the transmission technique, the optimal spectral bands were 560 ~ 590 nm and 760 ~ 810 nm at the VIS and NIR spectra, respectively. Later, the T-test and the IAD verified that the highest Rd values for discrimination were 600 ~ 640 nm and 800 ~ 840 nm at the VIS and NIR spectra, respectively. On the other side, the highest Tr values were 600 ~ 640 nm and 760 ~ 800 nm at the VIS and NIR spectra, respectively. The investigation’s average reading accuracy, sensitivity, and specificity were 85%, 81.88%, and 88.8%, respectively. The experimental trials revealed that the system could identify the optimal wavelength for therapeutic and diagnostic applications through the light interaction behavior of the breast tissue’s optical properties.