Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides [PDF]
Frontiers in Oncology, 11(2021), 4133, 2021 Objectives: To develop and validate a deep learning (DL)-based primary tumor biopsy signature for predicting axillary lymph node (ALN) metastasis preoperatively in early breast cancer (EBC) patients with clinically negative ALN. Methods: A total of 1,058 EBC patients with pathologically confirmed ALN status were enrolled from May 2010 to August 2020.
arxiv +1 more source
Initial validation of a virtual-reality learning environment for prostate biopsies: realism matters! [PDF]
Journal of Endourology and Part B, Videourology (2013) epub ahead
of print, 2013 : Introduction-objectives: A virtual-reality learning environment dedicated to prostate biopsies was designed to overcome the limitations of current classical teaching methods. The aim of this study was to validate reliability, face, content and construct of the simulator.
arxiv +1 more source
Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection [PDF]
, 2021 The Gleason scoring system is the primary diagnostic and prognostic tool for prostate cancer. In recent years, with the development of digitisation devices, the use of computer vision techniques for the analysis of biopsies has increased. However, to the best of the authors' knowledge, the development of algorithms to automatically detect individual ...
arxiv +1 more source
Using deep learning to detect patients at risk for prostate cancer despite benign biopsies [PDF]
arXiv, 2021 Background: Transrectal ultrasound guided systematic biopsies of the prostate is a routine procedure to establish a prostate cancer diagnosis. However, the 10-12 prostate core biopsies only sample a relatively small volume of the prostate, and tumour lesions in regions between biopsy cores can be missed, leading to a well-known low sensitivity to ...
arxiv
Prostate biopsy tracking with deformation estimation [PDF]
, 2011 Transrectal biopsies under 2D ultrasound (US) control are the current clinical standard for prostate cancer diagnosis. The isoechogenic nature of prostate carcinoma makes it necessary to sample the gland systematically, resulting in a low sensitivity. Also, it is difficult for the clinician to follow the sampling protocol accurately under 2D US control
arxiv +1 more source
TRUSformer: Improving Prostate Cancer Detection from Micro-Ultrasound Using Attention and Self-Supervision [PDF]
arXiv, 2023 A large body of previous machine learning methods for ultrasound-based prostate cancer detection classify small regions of interest (ROIs) of ultrasound signals that lie within a larger needle trace corresponding to a prostate tissue biopsy (called biopsy core).
arxiv
Computational Histological Staining and Destaining of Prostate Core Biopsy RGB Images with Generative Adversarial Neural Networks [PDF]
, 2018 Histopathology tissue samples are widely available in two states: paraffin-embedded unstained and non-paraffin-embedded stained whole slide RGB images (WSRI). Hematoxylin and eosin stain (H&E) is one of the principal stains in histology but suffers from several shortcomings related to tissue preparation, staining protocols, slowness and human error. We
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Lymphocyte Classification in Hyperspectral Images of Ovarian Cancer Tissue Biopsy Samples [PDF]
arXiv, 2022 Current methods for diagnosing the progression of multiple types of cancer within patients rely on interpreting stained needle biopsies. This process is time-consuming and susceptible to error throughout the paraffinization, Hematoxylin and Eosin (H&E) staining, deparaffinization, and annotation stages.
arxiv
Strategising template-guided needle placement for MR-targeted prostate biopsy [PDF]
arXiv, 2022 Clinically significant prostate cancer has a better chance to be sampled during ultrasound-guided biopsy procedures, if suspected lesions found in pre-operative magnetic resonance (MR) images are used as targets. However, the diagnostic accuracy of the biopsy procedure is limited by the operator-dependent skills and experience in sampling the targets ...
arxiv
High Accuracy Tumor Diagnoses and Benchmarking of Hematoxylin and Eosin Stained Prostate Core Biopsy Images Generated by Explainable Deep Neural Networks [PDF]
JAMA Network. 2020;3(5):e205111, 2019 Histopathological diagnoses of tumors in tissue biopsy after Hematoxylin and Eosin (H&E) staining is the gold standard for oncology care. H&E staining is slow and uses dyes, reagents and precious tissue samples that cannot be reused. Thousands of native nonstained RGB Whole Slide Image (RWSI) patches of prostate core tissue biopsies were registered ...
arxiv +1 more source