UniXGen: A Unified Vision-Language Model for Multi-View Chest X-ray Generation and Report Generation

Generated synthetic data in medical research can substitute privacy and security-sensitive data with a large-scale curated dataset, reducing data collection and annotation costs. As part of this effort, we propose UniXGen, a unified chest X-ray and report generation model, with the following contributions. First, we design a unified model for bidirectional chest X-ray and report generation by adopting a vector quantization method to discretize chest X-rays into discrete visual tokens and formulating both tasks as sequence generation tasks. Second, we introduce several special tokens to generate chest X-rays with specific views that can be useful when the desired views are unavailable. Furthermore, UniXGen can flexibly take various inputs from single to multiple views to take advantage of the additional findings available in other X-ray views. We adopt an efficient transformer for computational and memory efficiency to handle the long-range input sequence of multi-view chest X-rays with high resolution and long paragraph reports. In extensive experiments, we show that our unified model has a synergistic effect on both generation tasks, as opposed to training only the task-specific models. We also find that view-specific special tokens can distinguish between different views and properly generate specific views even if they do not exist in the dataset, and utilizing multi-view chest X-rays can faithfully capture the abnormal findings in the additional X-rays. The source code is publicly available at: https://github.com/ttumyche/UniXGen

Observation of the anomalous Hall effect in a layered polar semiconductor

Progress in magnetoelectric materials is hindered by apparently contradictory requirements for time-reversal symmetry broken and polar ferroelectric electronic structure in common ferromagnets and antiferromagnets. Alternative routes could be provided by recent discoveries of a time-reversal symmetry breaking anomalous Hall effect in noncollinear magnets and altermagnets, but hitherto reported bulk materials are not polar. Here, we report the observation of a spontaneous anomalous Hall effect in doped AgCrSe$_2$, a layered polar semiconductor with an antiferromagnetic coupling between Cr spins in adjacent layers. The anomalous Hall resistivity 3 $\mu\Omega$ cm is comparable to the largest observed in compensated magnetic systems to date, and is rapidly switched off when the angle of an applied magnetic field is rotated to $\sim 80^{\circ}$ from the crystalline $c$-axis. Our ionic gating experiments show that the anomalous Hall conductivity magnitude can be enhanced by modulating the $p$-type carrier density. We also present theoretical results that suggest the anomalous Hall effect is driven by Berry curvature due to noncollinear antiferromagnetic correlations among Cr spins, which are consistent with the previously suggested magnetic ordering in AgCrSe$_2$. Our results open the possibility to study the interplay of magnetic and ferroelectric-like responses in this fascinating class of materials.Comment: 8 pages, 5 figure

Observation of the anomalous Hall effect in a layered polar semiconductor

Funding: S.-J.K. acknowledged support from the International Max Planck Research School for Chemistry and Physics of Quantum Materials (IMPRS-CPQM). L.Š. acknowledged support from Johannes Gutenberg University Grant TopDyn, and support by the Deutsche Forschungsgemein- schaft (DFG, German Research Foundation) for funding through TRR 288 – 422213477 (projects A09 and B05).Progress in magnetoelectric materials is hindered by apparently contradictory requirements for time‐reversal symmetry broken and polar ferroelectric electronic structure in common ferromagnets and antiferromagnets. Alternative routes can be provided by recent discoveries of a time‐reversal symmetry breaking anomalous Hall effect (AHE) in noncollinear magnets and altermagnets, but hitherto reported bulk materials are not polar. Here, the authors report the observation of a spontaneous AHE in doped AgCrSe2, a layered polar semiconductor with an antiferromagnetic coupling between Cr spins in adjacent layers. The anomalous Hall resistivity 3 μΩcm is comparable to the largest observed in compensated magnetic systems to date, and is rapidly switched off when the angle of an applied magnetic field is rotated to ≈80° from the crystalline c‐axis. The ionic gating experiments show that the anomalous Hall conductivity magnitude can be enhanced by modulating the p‐type carrier density. They also present theoretical results that suggest the AHE is driven by Berry curvature due to noncollinear antiferromagnetic correlations among Cr spins, which are consistent with the previously suggested magnetic ordering in AgCrSe2. The results open the possibility to study the interplay of magnetic and ferroelectric‐like responses in this fascinating class of materials.Publisher PDFPeer reviewe

Spatializing an Artist-Resident Community Area at a Building-Level: A Case Study of Garosu-Gil, South Korea

This study integrated a focus on geographical, physical, and commercial characteristics to explore the commercial gentrification phenomenon and its related statistical summaries in the area of Garosu-gil in Seoul’s Sinsa-dong ward. In particular, this study first collected parcel and building data and corresponding attribute information and mapped the resulting datasets in a geographic information system (GIS) environment. We then examined gentrification issues per building and conducted statistical analyses to investigate spatial patterns of commercial gentrification, which were used to develop criteria for determining degrees of gentrification. Third, this study conducted correlation and regression analyses to quantify the strength of the linear relationship between pairs of variables associated with primary factors contributing to commercial gentrification, and used a geographically weighted regression model (GWR) to help understand and predict spatial relationships between significant variables. The results showed positive correlations between several variables and commercial gentrification in the study area, namely neighborhood-convenience facilities, building ages, store rents, new franchise and restaurant businesses, distance to subways, and the presence of multiple roads. Based on its finding, there are key contributions of this study as follows. The first significant contribution of this study is developing measurement of gentrification levels that can be used by policy makers at each of four stages of the gentrification process. Furthermore, this paper develops a comprehensive approach for spatially identifying gentrifying neighborhoods across multiple time periods in 2- and 3-dimensions. It eventually helps urban planners implement preventative or supportive programs to protect lower-income residents and small businesses and thereby engender more sustainable community development

Improved Lung Cancer Detection in Ultra Low dose CT with Combined AI-based Nodule Detection and Denoising Techniques

In this study, we evaluated the synergy between the two artificial intelligence solutions by applying the deep learning based denoising technique to determine if the performance of the AI-based lung nodule detection solution is enhanced.N

Growth of thymic epithelial tumors and thymic cysts: Differential radiological points

Background The growth rate of thymic epithelial tumors (TETs) and thymic cysts was investigated to determine whether they can be differentiated and clinico‐radiological predictors of interval growth was identified. Methods This retrospective study included 122 patients with pathologically proven thymic cysts (n = 56) or TETs (n = 66) who underwent two serial chest computed tomography scans at least eight weeks apart. Average diameters and attenuation were measured, volume‐doubling times (VDTs) were calculated, and clinical characteristics were recorded. VDTs were compared using the log‐rank test. Predictors of growth were analyzed using the log‐rank test and Cox regression analysis. Results The frequency of growth did not differ significantly between TETs and thymic cysts (P = 0.279). The VDT of thymic cysts (median 324 days) was not significantly different from that of the TETs (median 475 days; P = 0.808). Water attenuation (≤ 20 Hounsfield units) predicted growth in thymic cysts (P = 0.016; hazard ratio 13.2, 95% confidence interval 1.6–107.3), while lesion size (> 17.2 mm) predicted growth in TETs (P = 0.008 for size, P = 0.029 for size*time). For the growing lesions, the positive and negative predictive values of water attenuation for thymic cysts were 93% and 80%, respectively. Conclusion The frequencies of interval growth and VDTs were indistinguishable between TETs and thymic cysts. Water attenuation and lesion size predicted growth in thymic cysts and TETs, respectively. Among the growing lesions, water attenuation was a differential feature of thymic cysts

Tuning Resistive Switching Characteristics of Tantalum Oxide Memristors through Si Doping

An oxide memristor device changes its internal state according to the history of the applied voltage and current. The principle of resistive switching (RS) is based on ion transport (<i>e.g.</i>, oxygen vacancy redistribution). To date, devices with bi-, triple-, or even quadruple-layered structures have been studied to achieve the desired switching behavior through device structure optimization. In contrast, the device performance can also be tuned through fundamental atomic-level design of the switching materials, which can directly affect the dynamic transport of ions and lead to optimized switching characteristics. Here, we show that doping tantalum oxide memristors with silicon atoms can facilitate oxygen vacancy formation and transport in the switching layer with adjustable ion hopping distance and drift velocity. The devices show larger dynamic ranges with easier access to the intermediate states while maintaining the extremely high cycling endurance (>10¹⁰ set and reset) and are well-suited for neuromorphic computing applications. As an example, we demonstrate different flavors of spike-timing-dependent plasticity in this memristor system. We further provide a characterization methodology to quantitatively estimate the effective hopping distance of the oxygen vacancies. The experimental results are confirmed through detailed <i>ab initio</i> calculations which reveal the roles of dopants and provide design methodology for further optimization of the RS behavior

Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs

Objectives To develop and validate a deep learning-based prognostic model in patients with idiopathic pulmonary fibrosis (IPF) using chest radiographs.Methods To develop a deep learning-based prognostic model using chest radiographs (DLPM), the patients diagnosed with IPF during 2011-2021 were retrospectively collected and were divided into training (n = 1007), validation (n = 117), and internal test (n = 187) datasets. Up to 10 consecutive radiographs were included for each patient. For external testing, three cohorts from independent institutions were collected (n = 152, 141, and 207). The discrimination performance of DLPM was evaluated using areas under the time-dependent receiver operating characteristic curves (TD-AUCs) for 3-year survival and compared with that of forced vital capacity (FVC). Multivariable Cox regression was performed to investigate whether the DLPM was an independent prognostic factor from FVC. We devised a modified gender-age-physiology (GAP) index (GAP-CR), by replacing DLCO with DLPM.Results DLPM showed similar-to-higher performance at predicting 3-year survival than FVC in three external test cohorts (TD-AUC: 0.83 [95% CI: 0.76-0.90] vs. 0.68 [0.59-0.77], p &lt; 0.001; 0.76 [0.68-0.85] vs. 0.70 [0.60-0.80], p = 0.21; 0.79 [0.72-0.86] vs. 0.76 [0.69-0.83], p = 0.41). DLPM worked as an independent prognostic factor from FVC in all three cohorts (ps &lt; 0.001). The GAP-CR index showed a higher 3-year TD-AUC than the original GAP index in two of the three external test cohorts (TD-AUC: 0.85 [0.80-0.91] vs. 0.79 [0.72-0.86], p = 0.02; 0.72 [0.64-0.80] vs. 0.69 [0.61-0.78], p = 0.56; 0.76 [0.69-0.83] vs. 0.68 [0.60-0.76], p = 0.01).Conclusions A deep learning model successfully predicted survival in patients with IPF from chest radiographs, comparable to and independent of FVC.Clinical relevance statement Deep learning-based prognostication from chest radiographs offers comparable-to-higher prognostic performance than forced vital capacity.N

Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study.

To assess the effect of computer-aided detection (CAD) of brain metastasis (BM) on radiologists' diagnostic performance in interpreting three-dimensional brain magnetic resonance (MR) imaging using follow-up imaging and consensus as the reference standard.The institutional review board approved this retrospective study. The study cohort consisted of 110 consecutive patients with BM and 30 patients without BM. The training data set included MR images of 80 patients with 450 BM nodules. The test set included MR images of 30 patients with 134 BM nodules and 30 patients without BM. We developed a CAD system for BM detection using template-matching and K-means clustering algorithms for candidate detection and an artificial neural network for false-positive reduction. Four reviewers (two neuroradiologists and two radiology residents) interpreted the test set images before and after the use of CAD in a sequential manner. The sensitivity, false positive (FP) per case, and reading time were analyzed. A jackknife free-response receiver operating characteristic (JAFROC) method was used to determine the improvement in the diagnostic accuracy.The sensitivity of CAD was 87.3% with an FP per case of 302.4. CAD significantly improved the diagnostic performance of the four reviewers with a figure-of-merit (FOM) of 0.874 (without CAD) vs. 0.898 (with CAD) according to JAFROC analysis (p < 0.01). Statistically significant improvement was noted only for less-experienced reviewers (FOM without vs. with CAD, 0.834 vs. 0.877, p < 0.01). The additional time required to review the CAD results was approximately 72 sec (40% of the total review time).CAD as a second reader helps radiologists improve their diagnostic performance in the detection of BM on MR imaging, particularly for less-experienced reviewers

Limited detection of small (≤ 10 mm) colorectal liver metastasis at preoperative CT in patients undergoing liver resection

<div><p>Objective</p><p>To retrospectively determine the sensitivity of preoperative CT in the detection of small (≤ 10 mm) colorectal liver metastasis (CRLM) nodules in patients undergoing liver resection.</p><p>Methods</p><p>The institutional review board approved the study and waived informed consent. We included 461 pathologically confirmed CRLM nodules in 211 patients (including 71 women; mean age, 66.4 years) who underwent 229 liver resections following abdominal CT. Prior to 163 resections, gadoxetic acid-enhanced liver MR imaging was also performed. Nodules were matched between pathology reports and prospective CT reports following a predefined algorithm. Per-nodule sensitivity of CT was calculated by nodule-size category. Generalized estimating equations were used to adjust for within-case correlation.</p><p>Results</p><p>Fourteen nodule sizes were missing in the pathology report. Nodules of 1–5 mm and 6–10 mm accounted for 8.1% (n = 36) and 23.5% (n = 105) of the remaining 447 nodules, and the number of nodules gradually decreased as nodule size increased beyond 10 mm. The overall sensitivity of CT was 81.2% (95% confidence interval, 77.1%, 85.2%; 365/461). The sensitivity was 8% (0%, 17%; 3/36), 55% (45%, 65%; 59/105), 91%, 95%, and 100% for nodules of 1–5 mm, 6–10 mm, 11–15 mm, 16–20 mm, and >20 mm, respectively. The nodule-size distribution was similar between resections undergoing gadoxetic acid-enhanced MR imaging and those not undergoing the MR imaging.</p><p>Conclusion</p><p>CT has limited sensitivity for nodules of ≤ 10 mm and particularly of ≤ 5 mm.</p></div