Likelihood-Based Text-to-Image Evaluation with Patch-Level Perceptual and Semantic Credit Assignment

Text-to-image synthesis has made encouraging progress and attracted lots of public attention recently. However, popular evaluation metrics in this area, like the Inception Score and Fr'echet Inception Distance, incur several issues. First of all, they cannot explicitly assess the perceptual quality of generated images and poorly reflect the semantic alignment of each text-image pair. Also, they are inefficient and need to sample thousands of images to stabilise their evaluation results. In this paper, we propose to evaluate text-to-image generation performance by directly estimating the likelihood of the generated images using a pre-trained likelihood-based text-to-image generative model, i.e., a higher likelihood indicates better perceptual quality and better text-image alignment. To prevent the likelihood of being dominated by the non-crucial part of the generated image, we propose several new designs to develop a credit assignment strategy based on the semantic and perceptual significance of the image patches. In the experiments, we evaluate the proposed metric on multiple popular text-to-image generation models and datasets in accessing both the perceptual quality and the text-image alignment. Moreover, it can successfully assess the generation ability of these models with as few as a hundred samples, making it very efficient in practice

Neuroimaging Studies of Essential Tremor: How Well Do These Studies Support/Refute the Neurodegenerative Hypothesis?

Background: Tissue‐based research has recently led to a new patho‐mechanistic model of essential tremor (ET)—the cerebellar degenerative model. We are not aware of a study that has reviewed the current neuroimaging evidence, focusing on whether the studies support or refute the neurodegenerative hypothesis of ET. This was our aim. Methods: References for this review were identified by searches of PubMed (1966 to February 2014). Results: Several neuroimaging methods have been used to study ET, most of them based on magnetic resonance imaging (MRI). The methods most specific to address the question of neurodegeneration are MRI‐based volumetry, magnetic resonance spectroscopy, and diffusion‐weighted imaging. Studies using each of these methods provide support for the presence of cerebellar degeneration in ET, finding reduced cerebellar brain volumes, consistent decreases in cerebellar N‐acetylaspartate, and increased mean diffusivity. Other neuroimaging techniques, such as functional MRI and positron emission tomography (PET) are less specific, but still sensitive to potential neurodegeneration. These techniques are used for measuring a variety of brain functions and their impairment. Studies using these modalities also largely support cerebellar neuronal impairment. In particular, changes in 11C‐flumazenil binding in PET studies and changes in iron deposition in an MRI study provide evidence along these lines. The composite data point to neuronal impairment and likely neuronal degeneration in ET. Discussion: Recent years have seen a marked increase in the number of imaging studies of ET. As a whole, the combined data provide support for the presence of cerebellar neuronal degeneration in this disease

Reproducibility and effect of tissue composition on cerebellar GABA MRS in an elderly population.

Magnetic resonance spectroscopy (MRS) provides a valuable tool to non-invasively detect brain gamma-amino butyric acid (GABA) in vivo. GABAergic dysfunction has been observed in the aging cerebellum. Studying cerebellar GABA changes is of considerable interest in understanding certain age-related motor disorders. However, little is known about the reproducibility of GABA MRS in an aged population. Therefore, this study aimed to explore the feasibility and reproducibility of GABA MRS in the aged cerebellum at 3.0 Tesla and to examine the effect of differing tissue composition on GABA measurements. MRI and 1H MRS exams were performed on 10 healthy elderly volunteers (mean age 75.2 years ± 6.5 years) using a 3.0 Tesla Siemens Tim Trio scanner. Among them, 5 subjects were scanned twice to assess short-term reproducibility. The MEGA-PRESS J-editing sequence was used for GABA detection in two volumes of interest (VOIs) in left and right cerebellar dentate. MRS data processing and quantification were performed with LCModel 6.3-0L using two separate basis sets, generated from density matrix simulations using published values for chemical shifts an

A Pilot Study of Quantitative MRI Measurements of Ventricular Volume and Cortical Atrophy for the Differential Diagnosis of Normal Pressure Hydrocephalus

Current radiologic diagnosis of normal pressure hydrocephalus (NPH) requires a subjective judgment of whether lateral ventricular enlargement is disproportionate to cerebral atrophy based on visual inspection of brain images. We investigated whether quantitative measurements of lateral ventricular volume and total cortical thickness (a correlate of cerebral atrophy) could be used to more objectively distinguish NPH from normal controls (NC), Alzheimer's (AD), and Parkinson's disease (PD). Volumetric MRIs were obtained prospectively from patients with NPH (n = 5), PD (n = 5), and NC (5). Additional NC (n = 5) and AD patients (n = 10) from the ADNI cohort were examined. Although mean ventricular volume was significantly greater in the NPH group than all others, the range of values overlapped those of the AD group. Individuals with NPH could be better distinguished when ventricular volume and total cortical thickness were considered in combination. This pilot study suggests that volumetric MRI measurements hold promise for improving NPH differential diagnosis

Cingulate cortex hypoperfusion predicts Alzheimer's disease in mild cognitive impairment

BACKGROUND: Mild cognitive impairment (MCI) was recently described as a heterogeneous group with a variety of clinical outcomes and high risk to develop Alzheimer's disease (AD). Regional cerebral blood flow (rCBF) as measured by single photon emission computed tomography (SPECT) was used to study the heterogeneity of MCI and to look for predictors of future development of AD. METHODS: rCBF was investigated in 54 MCI subjects using Tc-99m hexamethylpropyleneamine oxime (HMPAO). An automated analysis software (BRASS) was applied to analyze the relative blood flow (cerebellar ratios) of 24 cortical regions. After the baseline examination, the subjects were followed clinically for an average of two years. 17 subjects progressed to Alzheimer's disease (PMCI) and 37 subjects remained stable (SMCI). The baseline SPECT ratio values were compared between PMCI and SMCI. Receiver operating characteristic (ROC) analysis was applied for the discrimination of the two subgroups at baseline. RESULTS: The conversion rate of MCI to AD was 13.7% per year. PMCI had a significantly decreased rCBF in the left posterior cingulate cortex, as compared to SMCI. Left posterior cingulate rCBF ratios were entered into a logistic regression model for ROC curve calculation. The area under the ROC curve was 74%–76%, which indicates an acceptable discrimination between PMCI and SMCI at baseline. CONCLUSION: A reduced relative blood flow of the posterior cingulate gyrus could be found at least two years before the patients met the clinical diagnostic criteria of AD

Mild cognitive impairment neuroimaging markers for early diagnosis of dementia

This thesis concerns the investigation of mild cognitive impairment (MCI) and Alzheimer's disease (AD) using single photon emission computed tomography (SPECT) and quantitative electroencepholography (qEEG). In study I, The qEEG values were cross-sectionally compared between AD, MCI and controls. AD had decreased global field power (GFP) and more anterior localization of three-dimensional dipole source in alpha and beta frequency. The results of longitudinal investigation of MCI showed a decreased alpha GFP and a more anterior localization of sources of theta, alpha and beta frequency in progressive mild cognitive impairment (PMCI), as compared to non-progressive mild cognitive impairment (SMCI). EEG values showed a moderate diagnostic accuracy in the study of AD and MCI. In study II & III, the baseline regional cerebral blood flow (rCBF) and neuropsychology were investigated in PMCI and SMCI. PMCI had decreased regional cerebral blood flow (rCBF) in posterior cingulate and parietal lobe as well as increased brain perfusion in prefrontal cortex compared to SMCI at baseline. The cognitive functions of PMCI were lower than SMCI with respect to episodic memory, visuospatial and general cognitive function represented by Mini-Mental State Examination (MMSE). Both SPECT and Neuropsychological test had moderate discriminant function between PMCI and SMCI at baseline and combining two methods can improve the diagnostic accuracy. In study IV, the longitudinal rCBF changes of PMCI and SMCI were investigated. SPECT data were analyzed with statistical parametric mapping (SPM) and BRASS program. No significant findings were detected using SPM. The results of BRASS showed a significant rCBF longitudinal reduction of PMCI in superior parietal lobe, parieto-temporal association cortex and medial temporal lobe and a significantly decreased general cognitive function represented by MMSE. To summarize, SPECT and EEG could provide promising markers for the early diagnosis of dementia and track the disease progression. Combining imaging investigation with neuropsychological testing may increase the diagnostic accuracy of preclinical dementia

Individual-level precision diagnosis for coronavirus disease 2019 related severe outcome: an early study in New York

Abstract Because of inadequate information provided by the on-going population level risk analyses for Coronavirus disease 2019 (COVID-19), this study aimed to evaluate the risk factors and develop an individual-level precision diagnostic method for COVID-19 related severe outcome in New York State (NYS) to facilitate early intervention and predict resource needs for patients with COVID-19. We analyzed COVID-19 related hospital encounter and hospitalization in NYS using Statewide Planning and Research Cooperative System hospital discharge dataset. Logistic regression was performed to evaluate the risk factors for COVID-19 related mortality. We proposed an individual-level precision diagnostic method by taking into consideration of the different weights and interactions of multiple risk factors. Age was the greatest risk factor for COVID-19 related fatal outcome. By adding other demographic variables, dyspnea or hypoxemia and multiple chronic co-morbid conditions, the model predictive accuracy was improved to 0.85 (95% CI 0.84–0.85). We selected cut-off points for predictors and provided a general recommendation to categorize the levels of risk for COVID-19 related fatal outcome, which can facilitate the individual-level diagnosis and treatment, as well as medical resource prediction. We further provided a use case of our method to evaluate the feasibility of public health policy for monoclonal antibody therapy