Journal review45 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. Pota et al., 2015, A SLUGGS and Gemini/GMOS combined study of the elliptical galaxyM60: wide-field photometry and kinematics of the globular cluster system # 세줄 요약 # We present new wide-field photometry and spectroscopy of the globular clusters (GCs) around NGC 4649 (M60), the third brightest galaxy in the Virgo cluster. We confirm significant GC colour bimodality and find that the red GCs are more centrally concentrated, while the blue GCs are more spatially extended. We find that formation via a major merger between two gas-poor galaxies, followe.. 2021. 8. 23. Kim et al., 2020, Active learning for accuracy enhancement of semantic segmentation with CNN-corrected label curations: Evaluation on kidney segmentation in abdominal CT # 세줄 요약 # Recent advances in fully convolutional networks have enabled automatic segmentation, however, high labeling efforts and difficulty in acquiring sufficient and high-quality training data is still a challenge. In this study, a cascaded 3D U-Net with active learning to 3 stages: first, training small dataset with manual labeling ground truth, second, training previous dataset and newly ad.. 2021. 8. 16. Shim et al., 2020, Automated rotator cuff tear classification using 3D convolutional neural network # 세줄 요약 # Rotator cuff tear (RCT) is one of the most common shoulder injuries. When diagnosing RCT, skilled orthopedists visually interpret magnetic resonance imaging (MRI) scan data. MRI data from 2,124 patients were used to train and test the VRN-based 3D CNN to classify RCT into five classes (None, Partial, Small, Medium, Large-to-Massive). The VRN-based 3D CNN outperformed orthopedists speci.. 2021. 8. 8. Blakeslee et al., 2012, Optical and Infrared Photometry of Globular Clusters in NGC 1399: Evidence for Color–Metarllicity Nonlinearity # 세줄요약 # We combine new Wide Field Camera 3 IR Channel (WFC3/IR) F160W (H160) imaging data for NGC 1399, the central galaxy in the Fornax cluster, with archival F475W (g475), F606W (V606), F814W (I814), and F850LP (z850) optical data from the Advanced Camera for Surveys (ACS). Consistent with the differing color distributions, the dependence of I814−H160 on g475−I814 for the matched GC sample is.. 2021. 8. 2. Kanavati et al., 2021, A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images # 세줄 요약 # The differentiation between major histological types of lung cancer, such as adenocarcinoma (ADC), squamous cell carcinoma (SCC), and small-cell lung cancer (SCLS) is of crucial importance for determining optimum cancer treatment. Hematoxylin and Eosin (H&E)-stained slides of small transbronchial lung biopsy (TBLB) are one of the primary sources for making a diagnosis, but if this diag.. 2021. 7. 18. Han et al., 2020, Predicting Unnecessary Nodule Biopsies from a Small, Unbalanced,and Pathologically Proven Dataset by Transfer Learning # 세줄요약 # The database includes 68 biopsied nodules, 16 are pathologically proven benign and the remaining 52 are malignant. The leave-one-out and 10-folder cross validations are applied to train and test the randomly selected 68 image slices (one image slice from one nodule) in each experiment. Transfer learning from other larger datasets can supply additional information to small and unbalanced.. 2020. 10. 6. Marcus et al., 2014, Brain PET in the Diagnosis of Alzheimer’s Disease # 세줄요약 # 알츠하이머 치매를 진단하는데 Brain PET 영상이 중요한 역할을 하며, 주로 FDG-PET 영상과 Amyloid PET 영상이 영상 판독에 사용된다. FDG-PET 영상을 통해 뇌 안에서 glucose metabolism(포도당 신진대사) 분포를 보고 AD(alzheimer disease)로 인한 치매와 그 외의 다른 치매들(frontotemporal dementia & Lewy body dementia)을 구별할 수 있다. Amyloid PET 영상이 중요한 이유는 치매가 아닌 정상 환자들도 나이가 들면서 생기는 Amyloid deposition(아밀로이드 퇴적) 현상을 배제하여, 알츠하이머 병 진단에만 적절한 임상 환경(Clinical setting)을 만들어주기 때문이다. # 상.. 2020. 7. 28. 이전 1 2 3 4 5 다음
