Leveraging Self-Supervised Vision Transformers for Neural Transfer Function Design

In volume rendering, transfer functions are used to classify structures of interest, and to assign optical properties such as color and opacity. They are commonly defined as 1D or 2D functions that map simple features to these optical properties. As the process of designing a transfer function is typically tedious and unintuitive, several approaches have been proposed for their interactive specification. In this paper, we present a novel method to define transfer functions for volume rendering by leveraging the feature extraction capabilities of self-supervised pre-trained vision transformers. To design a transfer function, users simply select the structures of interest in a slice viewer, and our method automatically selects similar structures based on the high-level features extracted by the neural network. Contrary to previous learning-based transfer function approaches, our method does not require training of models and allows for quick inference, enabling an interactive exploration of the volume data. Our approach reduces the amount of necessary annotations by interactively informing the user about the current classification, so they can focus on annotating the structures of interest that still require annotation. In practice, this allows users to design transfer functions within seconds, instead of minutes. We compare our method to existing learning-based approaches in terms of annotation and compute time, as well as with respect to segmentation accuracy. Our accompanying video showcases the interactivity and effectiveness of our method

Spatially Guiding Unsupervised Semantic Segmentation Through Depth-Informed Feature Distillation and Sampling

Traditionally, training neural networks to perform semantic segmentation required expensive human-made annotations. But more recently, advances in the field of unsupervised learning have made significant progress on this issue and towards closing the gap to supervised algorithms. To achieve this, semantic knowledge is distilled by learning to correlate randomly sampled features from images across an entire dataset. In this work, we build upon these advances by incorporating information about the structure of the scene into the training process through the use of depth information. We achieve this by (1) learning depth-feature correlation by spatially correlate the feature maps with the depth maps to induce knowledge about the structure of the scene and (2) implementing farthest-point sampling to more effectively select relevant features by utilizing 3D sampling techniques on depth information of the scene. Finally, we demonstrate the effectiveness of our technical contributions through extensive experimentation and present significant improvements in performance across multiple benchmark datasets

Neurocognitive deficits in depression: a systematic review of cognitive impairment in the acute and remitted state

Previous research suggests a broad range of deficits in major depressive disorder. Our goal was to update the current assumptions and investigate the extent of cognitive impairment in depression in the acute and remitted state. A systematic review of the existing literature between 2009 and 2019 assessing the risk of bias within the included studies was performed. Of the 42 articles reviewed, an unclear risk of bias was shown overall. The risk of bias mainly concerned the sample selection, inadequate remedial measures, as well as the lack of blinding the assessors. In the acute phase, we found strong support for impairment in processing speed, learning, and memory. Follow-up studies and direct comparisons revealed less pronounced deficits in remission, however, deficits were still present in attention, learning and memory, and working memory. A positive correlation between the number of episodes and cognitive deficits as well as depression severity and cognitive deficits was reported. The results also demonstrate a resemblance between the cognitive profiles in bipolar disorder and depression. Comparisons of depression with schizophrenia led to unclear results, at times suggesting an overlap in cognitive performance. The main findings support the global deficit hypothesis and align with results from prior meta-analyses and reviews. Recommendations for future research are also presented

Testing the accuracy of feldspar single grains to date late Holocene cyclone and tsunami deposits

Quartz is the preferred dosimeter for luminescence dating of Holocene sediments as optically stimulated luminescence (OSL) signals reset rapidly upon light exposure, and are stable over time. However, feldspar is required where quartz luminescence properties are inappropriate for dating, as is often the case in geologically young mountain ranges and areas with young volcanism. Here we aim to evaluate the potential of single grain feldspar luminescence dating applied to late Holocene cyclone and tsunami deposits, for which complete signal resetting can a priori not be guaranteed. To address potential problems of feldspar dating of such deposits associated with heterogeneous bleaching, remnant doses and anomalous fading, we use a low-temperature post infrared infrared stimulated luminescence protocol (pIRIR150) on single grains. For most samples, good agreement between fading corrected IR50 and non-fading corrected pIRIR150 ages is observed. Both feldspar ages generally also show good agreement with age control provided by historical data and quartz luminescence ages. pIRIR150 remnant ages in modern analogue samples are shown to be 150, IR50 and quartz ages, indicates that a significant number of grains must have experienced relatively complete signal resetting during or immediately prior to transport, as the three signals are known to bleach at different rates. Since light exposure during the event is expected to be limited, we deduce that a significant portion of the grains in the cyclone and tsunami deposits was already bleached prior to the event of interest. These well-bleached grains were likely eroded at the beach, while other grains with larger remnant ages probably originate from the shallow subtidal, coastal barriers or even further inland sources. Additional signal resetting during storm and tsunami transport is indicated by slightly younger quartz than feldspar ages for grains with incomplete pre-transport resetting that were eroded at the Holocene coastal barrier.</p

Free-Flap Reconstruction in Early-Stage Squamous Cell Carcinoma of the Oral Cavity : A Prospective Monocentric Trial to Evaluate Oncological Outcome and Quality of Life

Surgery is generally accepted as standard treatment in oral cancer, but the reconstructive procedures remain a matter of debate. The aim of this study was to evaluate oncological outcome and quality of life following surgical resection and free-flap reconstruction in patients with early oral squamous cell carcinoma. The presented trial was performed as a prospective, single-center observation study. Inclusion criteria were primary surgery in early-stage oral squamous cell carcinoma with free-flap reconstruction. Endpoints were overall and progression-free survival and quality of life up to 24 months after surgery. Twenty-six patients were included. Overall survival was 100% and progression-free survival was 92.3% in a maximum follow-up time of 21 months. Global quality of life showed no significant alteration after surgery. Patients reported a significant reduction in pain (p = 0.048) and a decreasing impairment of speech one year after surgery (p = 0.021). Free-flap reconstruction is a safe procedure that results in excellent oncological outcome and quality of life. Functional outcome is of high relevance in early-stage tumors of the head and neck and may mostly be affected by reconstructive procedures. Therefore, a prospective evaluation to explore success and the effects of surgical therapy is highly warranted

Finding Nano-\"Otzi: Semi-Supervised Volume Visualization for Cryo-Electron Tomography

Cryo-Electron Tomography (cryo-ET) is a new 3D imaging technique with unprecedented potential for resolving submicron structural detail. Existing volume visualization methods, however, cannot cope with its very low signal-to-noise ratio. In order to design more powerful transfer functions, we propose to leverage soft segmentation as an explicit component of visualization for noisy volumes. Our technical realization is based on semi-supervised learning where we combine the advantages of two segmentation algorithms. A first weak segmentation algorithm provides good results for propagating sparse user provided labels to other voxels in the same volume. This weak segmentation algorithm is used to generate dense pseudo labels. A second powerful deep-learning based segmentation algorithm can learn from these pseudo labels to generalize the segmentation to other unseen volumes, a task that the weak segmentation algorithm fails at completely. The proposed volume visualization uses the deep-learning based segmentation as a component for segmentation-aware transfer function design. Appropriate ramp parameters can be suggested automatically through histogram analysis. Finally, our visualization uses gradient-free ambient occlusion shading to further suppress visual presence of noise, and to give structural detail desired prominence. The cryo-ET data studied throughout our technical experiments is based on the highest-quality tilted series of intact SARS-CoV-2 virions. Our technique shows the high impact in target sciences for visual data analysis of very noisy volumes that cannot be visualized with existing techniques

Neurocognitive Deficits in First-Episode and Chronic Psychotic Disorders: A Systematic Review from 2009 to 2022

Cognitive impairment in patients suffering from schizophrenia spectrum disorders has been discussed as a strong predictor for multiple disease outcome variables, such as response to psychotherapy, stable relationships, employment, and longevity. However, the consistency and severity of cognitive deficits across multiple domains in individuals with first-episode and chronic psychotic disorders is still undetermined. We provide a comprehensive overview of primary research from the years 2009 to 2022. Based on a Cochrane risk assessment, a systematic synthesis of 51 out of 3669 original studies was performed. Impairment of cognitive functioning in patients diagnosed with first-episode psychotic disorders compared with healthy controls was predicted to occur in all assessed cognitive domains. Few overall changes were predicted for chronically affected patients relative to those in the first-episode stage, in line with previous longitudinal studies. Our research outcomes support the hypothesis of a global decrease in cognitive functioning in patients diagnosed with psychotic disorders, i.e., the occurrence of cognitive deficits in multiple cognitive domains including executive functioning, memory, working memory, psychomotor speed, and attention. Only mild increases in the frequency of cognitive impairment across studies were observed at the chronically affected stage relative to the first-episode stage. Our results confirm and extend the outcomes from prior reviews and meta-analyses. Recommendations for psychotherapeutic interventions are provided, considering the broad cognitive impairment already observed at the stage of the first episode. Based on the risk of bias assessment, we also make specific suggestions concerning the quality of future original studies

Surgical Treatment of Carcinomas of the Oral Minor Salivary Glands : Oncological Outcome in Dependence of Tumor Entity and Therapeutic Strategies

The aim of this study was to analyze the clinical outcomes of three types of minor salivary gland carcinomas (adenoid-cystic carcinomas (ACC), adeno carcinomas not otherwise specified (AC-NOS), and mucoepidermoid carcinomas (MEC)) after primary surgical therapy. A retrospective cohort study was designed and patients with cancer of the minor oral salivary glands treated in our department in the years 2011 to 2022 were included. Clinicopathological data were evaluated to compare overall survival and progression-free survival between the entities. Eighty-one patients were included. The rates of cervical metastases were 38.9% for ACC, 25% for MEC, and 9.1% for AC-NOS. ACC exhibited significantly higher rates of local and systemic disease recurrence (p = 0.02), and the presence of neck node metastases was confirmed as an independent prognostic factor for progressionfree survival (p = 0.014). Treatment success in terms of oncological outcome varied significantly between the different entities and implies different treatment regimens for each tumor entity