PROCEEDINGS VOLUME 10581
SPIE MEDICAL IMAGING | 10-15 FEBRUARY 2018
Medical Imaging 2018: Digital Pathology
Proceedings Volume 10581 is from: Logo
SPIE MEDICAL IMAGING
10-15 February 2018
Houston, Texas, United States
Keynote and Emerging Trends
Proc. SPIE 10581, Advancing cancer diagnostics with deep learning, 1058102 (); https://doi.org/10.1117/12.2291645
Proc. SPIE 10581, Creating synthetic digital slides using conditional generative adversarial networks: application to Ki67 staining, 1058103 (6 March 2018); https://doi.org/10.1117/12.2294999
Proc. SPIE 10581, Single stain normalization for IHC whole slide images, 1058104 (6 March 2018); https://doi.org/10.1117/12.2293587
Machine Learning Trends
Proc. SPIE 10581, SHIFT: speedy histopathological-to-immunofluorescent translation of whole slide images using conditional generative adversarial networks, 1058105 (6 March 2018); https://doi.org/10.1117/12.2293249
Proc. SPIE 10581, Tumor microenvironment for follicular lymphoma: structural analysis for outcome prediction, 1058106 (6 March 2018); https://doi.org/10.1117/12.2295284
Proc. SPIE 10581, Deep positive-unlabeled learning for region of interest localization in breast tissue images, 1058107 (6 March 2018); https://doi.org/10.1117/12.2293721
Proc. SPIE 10581, An application of transfer learning to neutrophil cluster detection for tuberculosis: efficient implementation with nonmetric multidimensional scaling and sampling, 1058108 (6 March 2018); https://doi.org/10.1117/12.2292249
Proc. SPIE 10581, Role of training data variability on classifier performance and generalizability, 1058109 (6 March 2018); https://doi.org/10.1117/12.2293919
Diagnosis, Prognosis, and Predictive Analysis
Proc. SPIE 10581, Computational analysis of the structural progression of human glomeruli in diabetic nephropathy, 105810A (6 March 2018); https://doi.org/10.1117/12.2295249
Proc. SPIE 10581, Examining structural changes in diabetic nephropathy using inter-nuclear distances in glomeruli: a comparison of variously automated methods, 105810B (6 March 2018); https://doi.org/10.1117/12.2295225
Proc. SPIE 10581, Deep variational auto-encoders for unsupervised glomerular classification, 105810C (6 March 2018); https://doi.org/10.1117/12.2295456
Proc. SPIE 10581, Combination of nuclear NF-kB/p65 localization and gland morphological features from surgical specimens appears to be predictive of early biochemical recurrence in prostate cancer patients, 105810D (6 March 2018); https://doi.org/10.1117/12.2292652
Proc. SPIE 10581, A bottom-up approach for tumour differentiation in whole slide images of lung adenocarcinoma, 105810E (6 March 2018); https://doi.org/10.1117/12.2293316
Proc. SPIE 10581, Mitotic cells detection for HEp-2 specimen images using threshold-based evaluation scheme, 105810F (6 March 2018); https://doi.org/10.1117/12.2293524
Detection and Segmentation
Proc. SPIE 10581, Quantifying cell-type interactions and their spatial patterns as prognostic biomarkers in follicular lymphoma, 105810G (6 March 2018); https://doi.org/10.1117/12.2293572
Proc. SPIE 10581, Automated T1 bladder risk stratification based on depth of lamina propria invasion from H and E tissue biopsies: a deep learning approach, 105810H (6 March 2018); https://doi.org/10.1117/12.2294552
Proc. SPIE 10581, Cancer detection in histopathology whole-slide images using conditional random fields on deep embedded spaces, 105810I (6 March 2018); https://doi.org/10.1117/12.2293107
Proc. SPIE 10581, Validation of multiplex immunohistochemistry assays using automated image analysis, 105810J (6 March 2018); https://doi.org/10.1117/12.2293168
Proc. SPIE 10581, Color deconvolution method with DAB scatter correction for bright field image analysis , 105810K (6 March 2018); https://doi.org/10.1117/12.2293576
Proc. SPIE 10581, Automatic color unmixing of IHC stained whole slide images, 105810L (6 March 2018); https://doi.org/10.1117/12.2293734
Precision Medicine and Grading
Proc. SPIE 10581, RaPtomics: integrating radiomic and pathomic features for predicting recurrence in early stage lung cancer, 105810M (6 March 2018); https://doi.org/10.1117/12.2296646
Proc. SPIE 10581, Deformable registration of histological cancer margins to gross hyperspectral images using demons, 105810N (6 March 2018); https://doi.org/10.1117/12.2293165
Proc. SPIE 10581, Localization and classification of cell nuclei in post-neoadjuvant breast cancer surgical specimen using fully convolutional networks, 105810O (6 March 2018); https://doi.org/10.1117/12.2292815
Proc. SPIE 10581, Context-based interpolation of coarse deep learning prediction maps for the segmentation of fine structures in immunofluorescence images, 105810P (6 March 2018); https://doi.org/10.1117/12.2292794
Proc. SPIE 10581, Automatic cancer detection and localization on prostatectomy histopathology images , 105810Q (6 March 2018); https://doi.org/10.1117/12.2292450
Poster Session
Proc. SPIE 10581, A watershed and feature-based approach for automated detection of lymphocytes on lung cancer images, 105810R (6 March 2018); https://doi.org/10.1117/12.2293147
Proc. SPIE 10581, Automated segmentation of epithelial tissue in prostatectomy slides using deep learning, 105810S (6 March 2018); https://doi.org/10.1117/12.2292872
Proc. SPIE 10581, Registration parameter optimization for 3D tissue modeling from resected tumors cut into serial H&E slides , 105810T (9 March 2018); https://doi.org/10.1117/12.2293962
Proc. SPIE 10581, Determining tumor cellularity in digital slides using ResNet, 105810U (6 March 2018); https://doi.org/10.1117/12.2292813
Proc. SPIE 10581, CNN based segmentation of nuclei in PAP-smear images with selective pre-processing, 105810X (6 March 2018); https://doi.org/10.1117/12.2293526
Proc. SPIE 10581, Tumor proliferation assessment of whole slide images, 105810Y (6 March 2018); https://doi.org/10.1117/12.2293634
Proc. SPIE 10581, H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection, 105810Z (6 March 2018); https://doi.org/10.1117/12.2293048
Proc. SPIE 10581, Simultaneous segmentation and classification of multichannel immuno-fluorescently labeled confocal microscopy images using deep convolutional neural networks , 1058110 (6 March 2018); https://doi.org/10.1117/12.2292934
Proc. SPIE 10581, Unsupervised pathology image segmentation using representation learning with spherical k-means, 1058111 (6 March 2018); https://doi.org/10.1117/12.2292172
Proc. SPIE 10581, Automatic segmentation of histopathological slides of renal tissue using deep learning, 1058112 (6 March 2018); https://doi.org/10.1117/12.2293717
Proc. SPIE 10581, Scalable storage of whole slide images and fast retrieval of tiles using Apache Spark, 1058113 (6 March 2018); https://doi.org/10.1117/12.2290380
Proc. SPIE 10581, Glomerular detection and segmentation from multimodal microscopy images using a Butterworth band-pass filter, 1058114 (6 March 2018); https://doi.org/10.1117/12.2295446
Proc. SPIE 10581, A performance comparison of low- and high-level features learned by deep convolutional neural networks in epithelium and stroma classification, 1058116 (6 March 2018); https://doi.org/10.1117/12.2292840
Proc. SPIE 10581, Image processing to extend effective OCT penetration depth in tissue, 1058117 (6 March 2018); https://doi.org/10.1117/12.2293650
Proc. SPIE 10581, Registration accuracy between whole slide images and glass slides in eeDAP workflow, 1058118 (6 March 2018); https://doi.org/10.1117/12.2293189
Proc. SPIE 10581, Classification of lung cancer histology images using patch-level summary statistics, 1058119 (6 March 2018); https://doi.org/10.1117/12.2293855
Proc. SPIE 10581, Segmentation of black ink and melanin in skin histopathological images, 105811A (6 March 2018); https://doi.org/10.1117/12.2292859
Proc. SPIE 10581, Semantic segmentation for prostate cancer grading by convolutional neural networks, 105811B (6 March 2018); https://doi.org/10.1117/12.2293000
Proc. SPIE 10581, SlideSeg: a Python module for the creation of annotated image repositories from whole slide images, 105811C (6 March 2018); https://doi.org/10.1117/12.2300262
Proc. SPIE 10581, An unsupervised network for fast microscopic image registration, 105811D (6 March 2018); https://doi.org/10.1117/12.2293264
Proc. SPIE 10581, Landmark-based reconstruction of 3D smooth structures from serial histological sections, 105811E (6 March 2018); https://doi.org/10.1117/12.2293510
Proc. SPIE 10581, Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears, 105811F (6 March 2018); https://doi.org/10.1117/12.2293762
Back to Top