Deep learning in histopathology: the path to the clinic

J Van der Laak, G Litjens, F Ciompi - Nature medicine, 2021 - nature.com
Abstract Machine learning techniques have great potential to improve medical diagnostics,
offering ways to improve accuracy, reproducibility and speed, and to ease workloads for …

Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - Medical image analysis, 2021 - Elsevier
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

Digital pathology and artificial intelligence

MKK Niazi, AV Parwani, MN Gurcan - The lancet oncology, 2019 - thelancet.com
In modern clinical practice, digital pathology has a crucial role and is increasingly a
technological requirement in the scientific laboratory environment. The advent of whole-slide …

Bach: Grand challenge on breast cancer histology images

G Aresta, T Araújo, S Kwok, SS Chennamsetty… - Medical image …, 2019 - Elsevier
Breast cancer is the most common invasive cancer in women, affecting more than 10% of
women worldwide. Microscopic analysis of a biopsy remains one of the most important …

Weakly supervised deep learning for whole slide lung cancer image analysis

X Wang, H Chen, C Gan, H Lin, Q Dou… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Histopathology image analysis serves as the gold standard for cancer diagnosis. Efficient
and precise diagnosis is quite critical for the subsequent therapeutic treatment of patients …

A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches

X Li, C Li, MM Rahaman, H Sun, X Li, J Wu… - Artificial Intelligence …, 2022 - Springer
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 …

Emerging role of deep learning‐based artificial intelligence in tumor pathology

Y Jiang, M Yang, S Wang, X Li… - Cancer communications, 2020 - Wiley Online Library
The development of digital pathology and progression of state‐of‐the‐art algorithms for
computer vision have led to increasing interest in the use of artificial intelligence (AI) …

Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges

G Murtaza, L Shuib, AW Abdul Wahab… - Artificial Intelligence …, 2020 - Springer
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …

[HTML][HTML] Methods for segmentation and classification of digital microscopy tissue images

QD Vu, S Graham, T Kurc, MNN To… - … in bioengineering and …, 2019 - frontiersin.org
High-resolution microscopy images of tissue specimens provide detailed information about
the morphology of normal and diseased tissue. Image analysis of tissue morphology can …

[HTML][HTML] Hierarchical graph representations in digital pathology

P Pati, G Jaume, A Foncubierta-Rodriguez… - Medical image …, 2022 - Elsevier
Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens
highly depend on the phenotype and topological distribution of constituting histological …