Recent functional magnetic resonance imaging (fMRI) experiments revealed similar neural representations across different types of two-dimensional (2-D) visual stimuli; however, real three-dimensional (3-D) objects affording action differentially affect neural activation and behavioral results relative to 2-D objects. Recruitment of multiple sensory regions during unisensory (visual, haptic, and auditory) object shape tasks suggests that shape representation may be modality invariant. This mini-review explores the overlapping neural regions involved in object shape representation, across 2-D, 3-D, visual, and haptic experiments.

OBJECTIVE: To evaluate and compare en face and 3-dimensional (3-D) properties of hypertransmission defects (HTDs) between different optical coherence tomography (OCT) devices using OCT volumes and reconstructed en face images.
METHODS: Comparative diagnostic evaluation study.
METHODS: Thirty eyes with dry age-related macular degeneration (AMD) that underwent dense OCT macular volume scans with both the Spectralis (97 B-scans/volume; 2910 B-scans in total) and Cirrus OCT (128 B-scans/volume; 3840 B-scans in total) from the Amish Eye Study cohort were included in this analysis. HTD regions were labeled on each B-scan and reconstructed into en face and 3-D volume images. Properties of HTD volume were compared between the 2 devices.
RESULTS: The qualitative score of en face images for HTD was higher for the Cirrus compared to the Spectralis (P < .01). The quality of Spectralis en face images improved after preprocessing and reconstruction. The 2-D HTD area on en face obtained from 2-D projections of 3-D volume did not differ between devices (P = .478, ICC = 0.998; Jaccard index 0.721 ± 0.086). There was no difference in the number, volume, PALs, and surface areas of HTDs between devices in the volumetric analysis (all P ≥ .090). The signal intensity of HTD normalized by the mean choroidal signal intensity did not differ between devices (P = .861).
CONCLUSIONS: The visualization of HTD on en face images from Spectralis OCT could be enhanced through image processing. The equivalence in 3-D HTD parameters between the 2 devices suggests interchangeability for assessing these lesions in AMD.

Electrical capacitance tomography (ECT) is a non-optical imaging technique in which a map of the interior permittivity of a volume is estimated by making capacitance measurements at its boundary and solving an inverse problem. While previous ECT demonstrations have often been at centimeter scales, ECT is not limited to macroscopic systems. In this paper, we demonstrate ECT imaging of polymer microspheres and bacterial biofilms using a CMOS microelectrode array, achieving spatial resolution of 10 microns. Additionally, we propose a deep learning architecture and an improved multi-objective training scheme for reconstructing out-of-plane permittivity maps from the sensor measurements. Experimental results show that the proposed approach is able to resolve microscopic 3-D structures, achieving 91.5% prediction accuracy on the microsphere dataset and 82.7% on the biofilm dataset, including an average of 4.6% improvement over baseline computational methods.

BACKGROUND: Supra aortic obstruction in children is uncommon and is seen in certain unique conditions. While intraluminal obstruction due to heavy calcification is seen in older populations, it is not described in pediatric populations. The coral reef aorta is a rare and distinct calcifying disease causing luminal obstruction of the suprarenal aorta in adults. The definition of this diagnosis relies entirely on the unique aspects and consistency of the lesions, which are rock-hard, irregular, gritty plaques with a white luminal surface resembling a coral reef. However, no such case has been described in children.
METHODS: We present an adolescent boy who presented with a heavily calcified ascending aortic lesion associated with aortopathy and hypertension, 12 years after an aortic coarctation repair. The investigations included echocardiography, magnetic resonance and computer-tomographic imaging. A 3-D model was printed in order to visualize and plan surgical steps in advance for safe placement of clamps and defining the extent of resection. In addition, it provided an idea about tissue quality, thickness, spatial relationship, and orientation in relation to surrounding structures. Successful resection and replacement of the diseased segment of the aorta were achieved on cardiopulmonary bypass support. Post-operative recovery was uneventful, and at 6-month follow-up, the patient is doing well. In this report, various aspects of such lesions have been discussed, including clinical presentations, complications, planning and conduct of a safe cardiopulmonary bypass, and precautions during surgery for a successful outcome.
CONCLUSIONS: Complicated obstructive aortic lesions in children require careful assessment, appropriate advanced imaging, and the use of 3-D printing technology in order to plan and perform safe and effective surgical management. The etiology of severe calcified aorta in children may be related to metabolic factors, previous surgery, use of a homograft, or an inflammatory process. However, it has yet to be proven.

This has become a significant study area in recent years because of its use in brain-machine interaction (BMI). The robustness problem of emotion classification is one of the most basic approaches for improving the quality of emotion recognition systems. One of the two main branches of these approaches deals with the problem by extracting the features using manual engineering and the other is the famous artificial intelligence approach, which infers features of EEG data. This study proposes a novel method that considers the characteristic behavior of EEG recordings and based on the artificial intelligence method. The EEG signal is a noisy signal with a non-stationary and non-linear form. Using the Empirical Wavelet Transform (EWT) signal decomposition method, the signal\'s frequency components are obtained. Then, frequency-based features, linear and non-linear features are extracted. The resulting frequency-based, linear, and nonlinear features are mapped to the 2-D axis according to the positions of the EEG electrodes. By merging this 2-D images, 3-D images are constructed. In this way, the multichannel brain frequency of EEG recordings, spatial and temporal relationship are combined. Lastly, 3-D deep learning framework was constructed, which was combined with convolutional neural network (CNN), bidirectional long-short term memory (BiLSTM) and gated recurrent unit (GRU) with self-attention (AT). This model is named EWT-3D-CNN-BiLSTM-GRU-AT. As a result, we have created framework comprising handcrafted features generated and cascaded from state-of-the-art deep learning models. The framework is evaluated on the DEAP recordings based on the person-independent approach. The experimental findings demonstrate that the developed model can achieve classification accuracies of 90.57 % and 90.59 % for valence and arousal axes, respectively, for the DEAP database. Compared with existing cutting-edge emotion classification models, the proposed framework exhibits superior results for classifying human emotions.

OBJECTIVE: Training computer-vision related algorithms on medical images for disease diagnosis or image segmentation is difficult in large part due to privacy concerns. For this reason, generative image models are highly sought after to facilitate data sharing. However, 3-D generative models are understudied, and investigation of their privacy leakage is needed.
METHODS: We introduce our 3-D generative model, Transversal GAN (TrGAN), using head & neck PET images which are conditioned on tumor masks as a case study. We define quantitative measures of image fidelity and utility, and propose a novel framework for evaluating privacy-utility trade-off through membership inference attack. These metrics are evaluated in the course of training to identify ideal fidelity, utility and privacy trade-offs and establish the relationships between these parameters.
RESULTS: We show that the discriminator of the TrGAN is vulnerable to attack, and that an attacker can identify which samples were used in training with almost perfect accuracy (AUC = 0.99). We also show that an attacker with access to only the generator cannot reliably classify whether a sample had been used for training (AUC = 0.51). We also propose and demonstrate a general decision procedure for any deep learning based generative model, which allows the user to quantify and evaluate the decision trade-off between downstream utility and privacy protection.
CONCLUSIONS: TrGAN can generate 3-D medical images that retain important image features and statistical properties of the training data set, with minimal privacy loss as determined by a membership inference attack. Our utility-privacy decision procedure may be beneficial to researchers who wish to share data or lack a sufficient number of large labeled image datasets.

We performed a systematic review to compare conventional (2-D) versus 3-D-guided corrective osteotomies regarding intraoperative results, patient-reported outcome measures, range of motion, incidence of complications and pain score. PubMed (MEDLINE), Embase and Cochrane CENTRAL were searched, and 53 articles were included, reporting 1257 patients undergoing forearm corrective osteotomies between 2010 and 2022. 3-D-guided surgery resulted in a greater improvement in median Disabilities of the Arm, Shoulder and Hand (DASH) score (28, SD 7 vs. 35, SD 5) and fewer complications (12% vs. 6%). Pain scores and range of motion were similar between 3-D-guided and conventional surgery. 3-D-guided corrective osteotomy surgery appears to improve patient-reported outcomes and reduce complications compared to conventional methods. However, due to the limited number of comparative studies and the heterogeneity of the studies, a large randomized controlled trial is needed to draw definitive conclusions.Level of evidence: III.

To evaluate the role of cone-beam computed tomography (CT) performed for the determination of the artery of Adamkiewicz (AKA) suspected by angiography during trans-catheter bronchial artery embolization for hemoptysis.
In this retrospective study, 17 patients with hemoptysis who underwent cone-beam CT for evaluation of the AKA prior to arterial embolization from December 2014 to March 2022 were included. During the angiographic session, two interventional radiologists selected the possible AKAs that were defined as obscured hairpin-curved vessels arising from the dorsal branch of the intercostal arteries and running towards the midline in the arterially enhanced phase. Contrast-enhanced cone-beam CT was performed as an adjunct to angiography to determine whether the indefinite AKA was a real AKA based on whether it was found to connect to the anterior spinal artery.
Selective cone-beam CT was performed at 17 possible AKAs detected by selective arteriogram of the intercostal artery (ICA). Cone-beam CT allowed for the determination of AKAs in 16 cases (94.1%). As a result of cone-beam CT findings, 9 of 16 study arteries (56.3%) were judged as definite AKAs, and the remaining 7 (43.7%) were judged as definitely not AKAs but as the musculocutaneous branching from the dorsal branch of the ICA. In 1 of 17 cases (5.9%), cone-beam CT could not determine the AKA because of poor image quality caused by inadequate breath holding. An additional anterior radiculomedullary artery arising from the dorsal branch of the lower ICA because of the inflow of the contrast medium through the anastomosis was detected in one case by conebeam CT but not by angiography.
Intraprocedural enhanced cone-beam CT performed as an adjunctive technique to angiography is sufficient for confident determination of the AKA, which is essential for the operators to perform accurate and safe arterial embolization for hemoptysis.

Using color Doppler flow imaging or high-definition flow imaging with three-dimensional volume or spatio-temporal image correlation (STIC) in the glass-body mode allows displaying both gray-scale and color information of the heart cycle-related flow events and vessel spatial relationship. Conventionally, STIC in the glass-body mode has been used to examine the fetal heart and assess heart defects. Recently, a novel application of STIC in the visualization of abdominal precordial veins and intraplacental vascularization in singleton pregnancies has been reported. The aim of this present review is to discuss the use of color Doppler with three- and four-dimensional ultrasonography in the evaluation of extracardiac, placental, umbilical cord and twin abnormalities with examples. The glass-body mode is complementary to conventional 2D ultrasonography. Further studies are required to investigate use of the glass-body mode in the assessment of intraplacental vascularization in singleton and twin pregnancies.

3-D cell cultures are being increasingly used as in vitro models are capable of better mimicry of in vivo tissues, particularly in drug screenings where mass transfer limitations can affect the cancer biology and response to drugs. Three-dimensional microscopy techniques, such as confocal and multiphoton microscopy, have been used to elucidate data from 3-D cell cultures and whole organs, but their reach inside the 3-D tissues is restrained by the light scattering of the tissues, limiting their effective reach to 100-200 µm, which is simply not enough. Tissue clearing protocols, developed mostly for larger specimens usually involve multiple steps of viscous liquid submersion, and are not easily adaptable for much smaller spheroids and organoids. In this work, we have developed a novel tissue clearing solution tailored for small spheroids and organoids. Our tissue clearing protocol, called HyClear, uses a mixture of DMSO, HPG and urea to allow for one-step tissue clearing of spheroids and organoids, and is compatible with high-throughput screening studies due to its speed and simplicity. We have shown that our tissue clearing agent is superior to many of the commonly used tissue clearing agents and allows for elucidating better quality data from drug screening experiments.