논문 리뷰62 van Dokkum et al, 2018, An Enigmatic Population of Luminous Globular Clusters in a Galaxy Lacking Dark Matter # 세줄 요약 # We recently found an ultra-diffuse galaxy (UDG) called NGC1052-DF2 with a half-light radius of Re = 2.2 kpc and little or no dark matter. Their properties are similar to ω Centauri (the brightest and largest globular cluster in the Milky Way), but that the luminosity function of metal-poor globular clusters is not universal and a factor of ∼1000 removed from the relation between globul.. 2022. 1. 2. Wang et al., 2019, Pathology Image Analysis Using Segmentation Deep Learning Algorithms. # 세줄 요약 # With the rapid development of image scanning techniques and visualization software, whole slide imaging (WSI) is becoming a routine diagnostic method. Deep learning-based pathology image segmentation has become an important tool in WSI analysis because that algorithms such as fully convolutional networks stand out for their accuracy, computational efficiency, and generalizability. In t.. 2021. 12. 20. [공저자] Lee et al., 2021, Performance evaluation in [18F]Florbetaben brain PET images classification using 3D Convolutional Neural Network # 세줄 요약 # We created and evaluated an [18F]Florbetaben amyloid brain positron emission tomography (PET) scan classification model with a Dong-A University Hospital (DAUH) dataset based on a convolutional neural network (CNN), and performed external validation with the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Three types of models were used, depending on their structure: The ac.. 2021. 10. 25. Hwang et al, 2019, Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs. # 세줄 요약 # To develop a deep learning-based algorithm that can classify normal and abnormal results from chest radiographs with major thoracic diseases (pulmonary malignant neoplasm, active tuberculosis, pneumonia, pneumothorax). This diagnostic study developed a deep learning-based algorithm using single-center data (chest radiographs: 54,221 normal findings; 35,613 abnormal findings) and extern.. 2021. 10. 20. [ResNet] He et al., 2015, Deep Residual Learning for Image Recognition # 세줄 요약 # We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We provide comprehensive empirical evidence showing that these residual networks are easier to optimize, and can gain accuracy from considerably increased depth (evaluate residual nets with a depth of up to 152 layers). This result won the 1st place on the.. 2021. 10. 17. Chies-Santos et al., 2012, An optical/NIR survey of globular clusters in early-type galaxies. III. On the colour bimodality of globular cluster systems # 세줄 요약 # We study optical/near-infrared (NIR) colour distributions of the GC systems in 14 E/S0 galaxies. We find that double-peaked colour distributions are more commonly seen in optical than in optical/NIR colours A bimodal optical colour distribution is not necessarily an indication of an underlying bimodal metallicity distribution. # 상세 리뷰 # 1. Introduction AIM: Study optical/NIR color dist.. 2021. 10. 10. Campanella et al., 2019, Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. # 세줄 요약 # The development of decision support systems for pathology and their deployment in clinical practice have been hindered by the need for large manually annotated datasets. We present a multiple instance learning-based deep learning system that uses only reported diagnoses as labels for training. Tests on prostate cancer, basal cell carcinoma and breast cancer metastases to axillary lymph.. 2021. 10. 4. Zhang et al., 2019, An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets # 세줄 요약 # Cancer has been one of the most threatening diseases, so our major goal is to identify malignant from benign lesions at radiology or CT imaging in the early stages, But it is difficult to collect such a large volume of images with pathological information. This paper explores two CNN models by focusing extensively on the expansion of training samples from two small pathologically prove.. 2021. 9. 27. Medina et al., 2020. Deep learning method for segmentation of rotator cuff muscles on MR images # 세줄 요약 # To develop and validate a deep convolutional neural network (CNN) method capable of (1) selecting a specific shoulder sagittal MR image (Y-view) and (2) automatically segmenting rotator cuff (RC) muscles on a Y-view. For model A, we manually selected shoulder sagittal T1 Y-view from 258 cases as ground truth to train a classification, For model B, we manually segmented subscapularis, s.. 2021. 9. 19. Cohen & Blakeslee & Ryzhov, 1998, The Ages and Abundances of a Large Sample of M87 Globular Clusters # 세줄 요약 # Combining the new (20 GCs; this paper) and existing data (150 GCs; Cohen & Ryzhov, 1997) for the galactic GCs (Globular clusters) and comparing the (U-R) colors and the line indices gave qualitative indications for the ages and abundances of M87 GC system. We find that the M87 GCs span a wide range in metallicity, from very metal-poor to somewhat above solar metallicity. The behavior o.. 2021. 8. 28. 이전 1 2 3 4 5 6 7 다음
