A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches
With the development of Computer-aided Diagnosis (CAD) and image scanning techniques,
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Deep learning in microscopy image analysis: A survey
Computerized microscopy image analysis plays an important role in computer aided
diagnosis and prognosis. Machine learning techniques have powered many aspects of …
diagnosis and prognosis. Machine learning techniques have powered many aspects of …
Detecting cancer metastases on gigapixel pathology images
Each year, the treatment decisions for more than 230,000 breast cancer patients in the US
hinge on whether the cancer has metastasized away from the breast. Metastasis detection is …
hinge on whether the cancer has metastasized away from the breast. Metastasis detection is …
Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
[HTML][HTML] Deep convolutional neural networks enable discrimination of heterogeneous digital pathology images
Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and
automated image analysis approaches have great potential to increase precision of …
automated image analysis approaches have great potential to increase precision of …
Deep learning in mammography and breast histology, an overview and future trends
A Hamidinekoo, E Denton, A Rampun, K Honnor… - Medical image …, 2018 - Elsevier
Recent improvements in biomedical image analysis using deep learning based neural
networks could be exploited to enhance the performance of Computer Aided Diagnosis …
networks could be exploited to enhance the performance of Computer Aided Diagnosis …
[HTML][HTML] Neutrophils dominate the immune cell composition in non-small cell lung cancer
J Kargl, SE Busch, GHY Yang, KH Kim… - Nature …, 2017 - nature.com
The response rate to immune checkpoint inhibitor therapy for non-small-cell lung cancer
(NSCLC) is just 20%. To improve this figure, several early phase clinical trials combining …
(NSCLC) is just 20%. To improve this figure, several early phase clinical trials combining …
Nuclei segmentation with recurrent residual convolutional neural networks based U-Net (R2U-Net)
Bio-medical image segmentation is one of the promising sectors where nuclei segmentation
from high-resolution histopathological images enables extraction of very high-quality …
from high-resolution histopathological images enables extraction of very high-quality …
The devil is in the details: Whole slide image acquisition and processing for artifacts detection, color variation, and data augmentation: A review
Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis
of different types of cancer. The preparation and digitization of histological tissues leads to …
of different types of cancer. The preparation and digitization of histological tissues leads to …
Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art
With the development of functional imaging modalities we now have the ability to study the
microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use …
microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use …