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21.
L. Umapathy G.G. Perez-Carrillo M.B. Keerthivasan J.A. Rosado-Toro M.I. Altbach B. Winegar C. Weinkauf A. Bilgin for the Alzheimers Disease Neuroimaging Initiative 《AJNR. American journal of neuroradiology》2021,42(4):639
BACKGROUND AND PURPOSE:Accurate and reliable detection of white matter hyperintensities and their volume quantification can provide valuable clinical information to assess neurologic disease progression. In this work, a stacked generalization ensemble of orthogonal 3D convolutional neural networks, StackGen-Net, is explored for improving automated detection of white matter hyperintensities in 3D T2-FLAIR images.MATERIALS AND METHODS:Individual convolutional neural networks in StackGen-Net were trained on 2.5D patches from orthogonal reformatting of 3D-FLAIR (n = 21) to yield white matter hyperintensity posteriors. A meta convolutional neural network was trained to learn the functional mapping from orthogonal white matter hyperintensity posteriors to the final white matter hyperintensity prediction. The impact of training data and architecture choices on white matter hyperintensity segmentation performance was systematically evaluated on a test cohort (n = 9). The segmentation performance of StackGen-Net was compared with state-of-the-art convolutional neural network techniques on an independent test cohort from the Alzheimer’s Disease Neuroimaging Initiative-3 (n = 20).RESULTS:StackGen-Net outperformed individual convolutional neural networks in the ensemble and their combination using averaging or majority voting. In a comparison with state-of-the-art white matter hyperintensity segmentation techniques, StackGen-Net achieved a significantly higher Dice score (0.76 [SD, 0.08], F1-lesion (0.74 [SD, 0.13]), and area under precision-recall curve (0.84 [SD, 0.09]), and the lowest absolute volume difference (13.3% [SD, 9.1%]). StackGen-Net performance in Dice scores (median = 0.74) did not significantly differ (P = .22) from interobserver (median = 0.73) variability between 2 experienced neuroradiologists. We found no significant difference (P = .15) in white matter hyperintensity lesion volumes from StackGen-Net predictions and ground truth annotations.CONCLUSIONS:A stacked generalization of convolutional neural networks, utilizing multiplanar lesion information using 2.5D spatial context, greatly improved the segmentation performance of StackGen-Net compared with traditional ensemble techniques and some state-of-the-art deep learning models for 3D-FLAIR.White matter hyperintensities (WMHs) correspond to pathologic features of axonal degeneration, demyelination, and gliosis observed within cerebral white matter.1 Clinically, the extent of WMHs in the brain has been associated with cognitive impairment, Alzheimer’s disease and vascular dementia, and increased risk of stroke.2,3 The detection and quantification of WMH volumes to monitor lesion burden evolution and its correlation with clinical outcomes have been of interest in clinical research.4,5 Although the extent of WMHs can be visually scored,6 the categoric nature of such scoring systems makes quantitative evaluation of disease progression difficult. Manually segmenting WMHs is tedious, prone to inter- and intraobserver variability, and is, in most cases, impractical. Thus, there is an increased interest in developing fast, accurate, and reliable computer-aided automated techniques for WMH segmentation.Convolutional neural network (CNN)-based approaches have been successful in several semantic segmentation tasks in medical imaging.7 Recent works have proposed using deep learning–based methods for segmenting WMHs using 2D-FLAIR images.8-11 More recently, a WMH segmentation challenge12 was also organized (http://wmh.isi.uu.nl/) to facilitate comparison of automated segmentation of WMHs of presumed vascular origin in 2D multislice T2-FLAIR images. Architectures that used an ensemble of separately trained CNNs showed promising results in this challenge, with 3 of the top 5 winners using ensemble-based techniques.12Conventional 2D-FLAIR images are typically acquired with thick slices (3–4 mm) and possible slice gaps. Partial volume effects from a thick slice are likely to affect the detection of smaller lesions, both in-plane and out-of-plane. 3D-FLAIR images, with isotropic resolution, have been shown to achieve higher resolution and contrast-to-noise ratio13 and have shown promising results in MS lesion detection using 3D CNNs.14 Additionally, the isotropic resolution enables viewing and evaluation of the images in multiple planes. This multiplanar reformatting of 3D-FLAIR without the use of interpolating kernels is only possible due to the isotropic nature of the acquisition. Network architectures that use information from the 3 orthogonal views have been explored in recent works for CNN-based segmentation of 3D MR imaging data.15 The use of data from multiple planes allows more spatial context during training without the computational burden associated with full 3D training.16 The use of 3 orthogonal views simultaneously mirrors how humans approach this segmentation task.Ensembles of CNNs have been shown to average away the variances in the solution and the choice of model- and configuration-specific behaviors of CNNs.17 Traditionally, the solutions from these separately trained CNNs are combined by averaging or using a majority consensus. In this work, we propose the use of a stacked generalization framework (StackGen-Net) for combining multiplanar lesion information from 3D CNN ensembles to improve the detection of WMH lesions in 3D-FLAIR. A stacked generalization18 framework learns to combine solutions from individual CNNs in the ensemble. We systematically evaluated the performance of this framework and compared it with traditional ensemble techniques, such as averaging or majority voting, and state-of-the-art deep learning techniques. 相似文献
22.
Andres Eduardo Campuzano-García Bertha Torres-Alvarez Diana Hernández-Blanco 《Journal of cosmetic and laser therapy》2015,17(4):213-215
Hailey–Hailey disease (HHD), also known as benign familial pemphigus, is an autosomal dominant skin condition that affects the adhesion of epidermal keratinocytes. Although the initial manifestation of flaccid vesicles on erythematous or normal skin in flexure sites frequently goes unnoticed, large, macerated, exudative plaques of superficial erosions with crusting are observed at the time of diagnosis. There is no specific treatment for HHD, and most cases are symptomatically supported. However, infrared laser ablation has been somewhat helpful. We present a case successfully treated with fractional CO2 laser showing a long-term favourable outcome and no adverse effects. Thus, this modality could be an alternative to full ablation for this condition. 相似文献
23.
Alejandra Gordillo Hernández Eduardo Dominguez-Adame Lanuza Auxiliadora Cano Matias Rosario Perez Huertas Katherine Maria Gallardo Rodriguez Purificacion Gallinato Perez Fernando Oliva Mompean 《World journal of gastrointestinal surgery》2015,7(8):170-173
Gangliocytic paragangliomas are rare tumors that almost exclusively occur within the second portion of the duodenum. Although these tumors generally have a benign clinical course, they have the potential to recur or metastasize to regional lymph nodes. The case report presented here describes a 57-year-old female patient with melena, progressive asthenia, anemia, and a mass in the second-third portion of the duodenum that was treated by local excision. The patient was diagnosed with a friable bleeding tumor. The histologic analysis showed that the tumor was a 4 cm gangliocytic paraganglioma without a malignant cell pattern. In the absence of local invasion or distant metastasis, endoscopic resection represents a feasible, curative therapy. Although endoscopic polypectomy is currently considered the treatment of choice, it is not recommended if the size of the tumor is > 3 cm and/or there is active or recent bleeding. Patients diagnosed with a gangliocytic paraganglioma should be closely followed-up for possible local recurrence. 相似文献
24.
Primary cutaneous anaplastic large cell lymphomas with 6p25.3 rearrangement exhibit particular histological features
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Francisca Morgado Mariana Batista Ana Moreno Inês Coutinho 《Pediatric dermatology》2021,38(1):191-193
We present a 6‐year‐old girl with skin hyperpigmentation, leukoplakia, and onychodystrophy, the classic mucocutaneous triad usually associated with dyskeratosis congenita. The patient also had premature graying of the hair, bone marrow failure, hepatitis, exudative retinopathy, osteopenia with multiple long bone fractures, and intracranial calcifications and brain cysts. Coats plus syndrome is a rare disease with a clinical and genetic overlap with dyskeratosis congenita. This disease is reviewed, with a focus on the pathogenesis of the genetic anomalies and its background as a telomere biology disorder. 相似文献
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Rosario Gulias-Cañizo Anell Lagunes-Guillén Arturo González-Robles Erika Sánchez-Guzmán Federico Castro-Muñozledo 《Burns : journal of the International Society for Burn Injuries》2019,45(2):398-412