Cone beam computed tomography (CBCT) technology is increasingly utilized in the head and neck region and is valuable in treatment planning for cleft palate patients, potentially enabling the creation of 3D-printed obturators to assist with feeding and speech. This technical report investigates the feasibility of using data from a 360-degree CBCT scan to accurately produce a cleft palate obturator and assesses whether a lower-dose 180-degree CBCT scan can achieve a comparable result. A simulated cleft palate was crafted on a dehydrated human skull, which was then scanned using both 360-degree and 180-degree CBCT scanning protocols. Two obturators were digitally designed based on the segmented images from each scan and subsequently 3D printed. Evaluation of the segmented images and 3D-printed obturators from both protocols demonstrated clear visualization of anatomical landmarks and identical scores across all parameters, suggesting that the 180-degree CBCT scan can produce an obturator of comparable quality to that of the 360-degree scan, with the added benefit of reduced radiation exposure.

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BACKGROUND: Image-guided neurosurgery requires high localization and registration accuracy to enable effective treatment and avoid complications. However, accurate neuronavigation based on preoperative magnetic resonance (MR) or computed tomography (CT) images is challenged by brain deformation occurring during the surgical intervention.
OBJECTIVE: To facilitate intraoperative visualization of brain tissues and deformable registration with preoperative images, a 3D deep learning (DL) reconstruction framework (termed DL-Recon) was proposed for improved intraoperative cone-beam CT (CBCT) image quality.
METHODS: The DL-Recon framework combines physics-based models with deep learning CT synthesis and leverages uncertainty information to promote robustness to unseen features. A 3D generative adversarial network (GAN) with a conditional loss function modulated by aleatoric uncertainty was developed for CBCT-to-CT synthesis. Epistemic uncertainty of the synthesis model was estimated via Monte Carlo (MC) dropout. Using spatially varying weights derived from epistemic uncertainty, the DL-Recon image combines the synthetic CT with an artifact-corrected filtered back-projection (FBP) reconstruction. In regions of high epistemic uncertainty, DL-Recon includes greater contribution from the FBP image. Twenty paired real CT and simulated CBCT images of the head were used for network training and validation, and experiments evaluated the performance of DL-Recon on CBCT images containing simulated and real brain lesions not present in the training data. Performance among learning- and physics-based methods was quantified in terms of structural similarity (SSIM) of the resulting image to diagnostic CT and Dice similarity metric (DSC) in lesion segmentation compared to ground truth. A pilot study was conducted involving seven subjects with CBCT images acquired during neurosurgery to assess the feasibility of DL-Recon in clinical data.
RESULTS: CBCT images reconstructed via FBP with physics-based corrections exhibited the usual challenges to soft-tissue contrast resolution due to image non-uniformity, noise, and residual artifacts. GAN synthesis improved image uniformity and soft-tissue visibility but was subject to error in the shape and contrast of simulated lesions that were unseen in training. Incorporation of aleatoric uncertainty in synthesis loss improved estimation of epistemic uncertainty, with variable brain structures and unseen lesions exhibiting higher epistemic uncertainty. The DL-Recon approach mitigated synthesis errors while maintaining improvement in image quality, yielding 15%-22% increase in SSIM (image appearance compared to diagnostic CT) and up to 25% increase in DSC in lesion segmentation compared to FBP. Clear gains in visual image quality were also observed in real brain lesions and in clinical CBCT images.
CONCLUSIONS: DL-Recon leveraged uncertainty estimation to combine the strengths of DL and physics-based reconstruction and demonstrated substantial improvements in the accuracy and quality of intraoperative CBCT. The improved soft-tissue contrast resolution could facilitate visualization of brain structures and support deformable registration with preoperative images, further extending the utility of intraoperative CBCT in image-guided neurosurgery.

Coded Aperture (CA) imaging has recently been used in nuclear medicine, but still, there is no commercial SPECT imaging camera based on CA for cancer detection. The literature is rich in examples of using the CA for planar and thin 3D imaging. However, thick 3D reconstruction is still challenging for small lesion detection. This paper presents the results of mosaic modified uniformly redundant array (MURA) mask/antimask CA combined with a maximum-likelihood expectation-maximization (MLEM) algorithm. The MLEM is an iterative algorithm applied to a mosaic MURA CA mask/antimask for 3D anthropomorphic breast phantom reconstruction, slice by slice. The difference between the mask and the antimask suppresses the background noise to enhance the quality of reconstructed images. Furthermore, all reconstructed slices are stacked to form a 3D breast phantom image from single-projection data. The results of phantom reconstruction with 8 mm, 6 mm, 4 mm, and 3 mm lesions are presented. Moreover, the proposed SPECT imaging camera can reconstruct a 3D breast phantom from single-projection data of the patient\'s scanning. To assess the quality of lesions in the reconstructed images, the contrast-to-background ratio (CBR), the peak signal-to-noise ratio (PSNR) and mean square error (MSE) were measured.

We have explored the intracellular cell organelle\'s structural alterations after photodynamic treatment with chlorin p6 -histamine conjugate (Cp6 -his) in human oral cancer cells. Herein, the cells were treated with Cp6 -his (10 μm) and counterstained with organelle-specific fluorescence probes to find the site of intracellular localization using confocal microscopy. For photodynamic therapy (PDT), the cells were exposed to ~30 kJ/m2 red light (660 ± 20 nm) to induce ~90% cytotoxicity. We used the three-dimensional (3D) image reconstruction approach to analyze the photodynamic damage to cell organelles. The result showed that Cp6 -his localized mainly in the endoplasmic reticulum (ER) and lysosomes but not in mitochondria and Golgi apparatus (GA). The 3D model revealed that in necrotic cells, PDT led to extensive fragmentation of ER and fragmentation and swelling of GA as well. Results suggest that the indirect damage to GA occurred due to loss of connection between ER and GA. Moreover, in damaged cells with no sign of necrosis, the perinuclear ER appeared condensed and surrounded by several small clumps at the peripheral region of the cell, and the GA was observed to form a single condensed structure. Since these structural changes were associated with apoptotic cell death, it is suggested that the necrotic and apoptotic death induced by PDT with Cp6 -his is determined by the severity of damage to ER and indirect damage to GA. The results suggest that the indirect damage to cell organelle apart from the sites of photosensitizer localization and the severity of damage at the organelle level contribute significantly to the mode of cell death in PDT.

The reconstruction of a volumetric image from Digital Breast Tomosynthesis (DBT) measurements is an ill-posed inverse problem, for which existing iterative regularized approaches can provide a good solution. However, the clinical task is somehow omitted in the derivation of those techniques, although it plays a primary role in the radiologist diagnosis. In this work, we address this issue by introducing a novel variational formulation for DBT reconstruction, tailored for a specific clinical task, namely the detection of microcalcifications. Our method aims at simultaneously enhancing the detectability performance and enabling a high-quality restoration of the background breast tissues. Our contribution is threefold. First, we introduce an original task-based reconstruction framework through the proposition of a detectability function inspired from mathematical model observers. Second, we propose a novel total-variation regularizer where the gradient field accounts for the different morphological contents of the imaged breast. Third, we integrate the two developed measures into a cost function, minimized thanks to a new form of the Majorize Minimize Memory Gradient (3MG) algorithm. We conduct a numerical comparison of the convergence speed of the proposed method with those of standard convex optimization algorithms. Experimental results show the interest of our DBT reconstruction approach, qualitatively and quantitatively.

Microscopy, which is listed among the major in-situ imaging applications, allows to derive information from a biological sample on the existing architectural structures of cells and tissues and their changes over time. Large biological samples such as tumor spheroids cannot be imaged within one field of view, regional imaging in different areas and subsequent stitching are required to attain the full picture. Microscopy is not typically used to produce full-size visualization of tumor spheroids measuring a few millimeters in size. In this study, we propose a 3D volume imaging technique for tracing the growth of an entire tumor spheroid measuring up to 10 mm using a miniaturized optical (mini-Opto) tomography platform. We performed a primary analysis of the 3D imaging for the MIA PaCa-2 pancreatic tumoroid employing its 2D images produced with the mini-Opto tomography from different angles ranging from -25 ° to +25 ° at six different three-day-apart time points of consecutive image acquisition. These 2D images were reconstructed by using a 3D image reconstruction algorithm that we developed based on the algebraic reconstruction technique (ART). We were able to reconstruct the 3D images of the tumoroid to achieve 800 × 800-pixel 50-layer images at resolutions of 5-25 μm. We also created its 3D visuals to understand more clearly how its volume changed and how it looked over weeks. The volume of the tumor was calculated to be 6.761 mm3 at the first imaging time point and 46.899 mm3 15 days after the first (at the sixth time point), which is 6.94 times larger in volume. The mini-Opto tomography can be considered more advantageous than commercial microscopy because it is portable, more cost-effective, and easier to use, and enables full-size visualization of biological samples measuring a few millimeters in size.

Most methods that model 3D porous media from 2D images are based on binary images. In this paper, we propose a method for reconstructing 3D greyscale isotropic porous media images from a single image. Our proposed method incorporates a fast-sampling procedure to control the continuity and variability between adjoining reconstruction layers, a new similarity calculation method to obtain the most similar patterns from a pattern dictionary, and a central area simulation procedure to solve the block effect problem. The reconstruction results from application of our proposed method to a real reservoir 3D model obtained via computed tomography (CT) and a comparison with the original CT structure demonstrate that our proposed method can reproduce properties such as autocorrelation function, linear function, shape distribution, average shape factor, average pore radius size, average throat radius size, average pore volume, permeability and grey histogram. Further, the comparison results indicate that the statistical characteristics of the reconstructions match the training image and the CT model perfectly.

BACKGROUND: The surgical indications for liver hemangioma remain unclear.
METHODS: Data from 152 patients with hepatic hemangioma who underwent hepatectomy between 2004 and 2019 were retrospectively reviewed. We analyzed characteristics including tumor size, surgical parameters, and variables associated with Kasabach-Merritt syndrome and compared the outcomes of laparoscopic and open hepatectomy. Here, we describe surgical techniques for giant hepatic hemangioma and report on two meaningful cases.
RESULTS: Most (63.8%) patients with hepatic hemangioma were asymptomatic. Most (86.4%) tumors from patients with Kasabach-Merritt syndrome were larger than 15 cm. Enucleation (30.9%), sectionectomy (28.9%), hemihepatectomy (25.7%), and the removal of more than half of the liver (14.5%) were performed through open (87.5%) and laparoscopic (12.5%) approaches. Laparoscopic hepatectomy is associated with an operative time, estimated blood loss, and major morbidity and mortality rate similar to those of open hepatectomy, but a shorter length of stay. 3D image reconstruction is an alternative for diagnosis and surgical planning for partial hepatectomy.
CONCLUSIONS: The main indication for surgery is giant (> 10 cm) liver hemangioma, with or without symptoms. Laparoscopic hepatectomy was an effective option for hepatic hemangioma treatment. For extremely giant hemangiomas, 3D image reconstruction was indispensable. Hepatectomy should be performed by experienced hepatic surgeons.

Accurate measurements of food volume and density are often required as \'gold standards\' for calibration of image-based dietary assessment and food database development. Currently, there is no specialised laboratory instrument for these measurements. We present the design of a new volume of density (VD) meter to bridge this technological gap.
Our design consists of a turntable, a load sensor, a set of cameras and lights installed on an arc-shaped stationary support, and a microcomputer. It acquires an array of food images, reconstructs a 3D volumetric model, weighs the food and calculates both food volume and density, all in an automatic process controlled by the microcomputer. To adapt to the complex shapes of foods, a new food surface model, derived from the electric field of charged particles, is developed for 3D point cloud reconstruction of either convex or concave food surfaces.
We conducted two experiments to evaluate the VD meter. The first experiment utilised computer-synthesised 3D objects with prescribed convex and concave surfaces of known volumes to investigate different food surface types. The second experiment was based on actual foods with different shapes, colours and textures. Our results indicated that, for synthesised objects, the measurement error of the electric field-based method was <1 %, significantly lower compared with traditional methods. For real-world foods, the measurement error depended on the types of food volumes (detailed discussion included). The largest error was approximately 5 %.
The VD meter provides a new electronic instrument to support advanced research in nutrition science.