AIMC Topic: Cytodiagnosis

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Diagnosing thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance cytology with the deep convolutional neural network.

Scientific reports
To compare the diagnostic performances of physicians and a deep convolutional neural network (CNN) predicting malignancy with ultrasonography images of thyroid nodules with atypia of undetermined significance (AUS)/follicular lesion of undetermined s...

Segmentation of Overlapping Cervical Cells with Mask Region Convolutional Neural Network.

Computational and mathematical methods in medicine
The task of segmenting cytoplasm in cytology images is one of the most challenging tasks in cervix cytological analysis due to the presence of fuzzy and highly overlapping cells. Deep learning-based diagnostic technology has proven to be effective in...

Robust whole slide image analysis for cervical cancer screening using deep learning.

Nature communications
Computer-assisted diagnosis is key for scaling up cervical cancer screening. However, current recognition algorithms perform poorly on whole slide image (WSI) analysis, fail to generalize for diverse staining and imaging, and show sub-optimal clinica...

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

Scientific reports
With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerned on the current classification system of International Classification of Diseases, Tenth Revision (...

A deep learning system to diagnose the malignant potential of urothelial carcinoma cells in cytology specimens.

Cancer cytopathology
BACKGROUND: Although deep learning algorithms for clinical cytology have recently been developed, their application to practical assistance systems has not been achieved. In addition, whether deep learning systems (DLSs) can perform diagnoses that ca...

Deep learning based digital cell profiles for risk stratification of urine cytology images.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Urine cytology is a test for the detection of high-grade bladder cancer. In clinical practice, the pathologist would manually scan the sample under the microscope to locate atypical and malignant cells. They would assess the morphology of these cells...

The emerging role of deep learning in cytology.

Cytopathology : official journal of the British Society for Clinical Cytology
Deep learning (DL) is a component or subset of artificial intelligence. DL has contributed significant change in feature extraction and image classification. Various algorithmic models are used in DL such as a convolutional neural network (CNN), recu...

Challenges Developing Deep Learning Algorithms in Cytology.

Acta cytologica
BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cyt...

Developing a Machine Learning Algorithm for Identifying Abnormal Urothelial Cells: A Feasibility Study.

Acta cytologica
INTRODUCTION: Urine cytology plays an important role in diagnosing urothelial carcinoma (UC). However, urine cytology interpretation is subjective and difficult. Morphogo (ALAB, Boston, MA, USA), equipped with automatic acquisition and scanning, opti...