Pathology

Segmentation of glandular epithelium in colorectal tumours to automatically compartmentalise IHC biomarker quantification: A deep learning approach.

In this paper, we propose a method for automatically annotating slide images from colorectal tissue samples. Our objective is to segment glandular epithelium in histological images from tissue slides submitted to different staining techniques, including usual haematoxylin-eosin (H&E) as well as immunohistochemistry (IHC). The proposed method makes use of Deep Learning and is based on a new convolu...

Comparison of Robot-Assisted Versus Open Simple Prostatectomy for Benign Prostatic Hyperplasia.

PURPOSE OF REVIEW: Recent advancements in minimally invasive approaches for prostate surgery have provided numerous options for surgical management of benign prostatic hyperplasia (BPH). In the setting of a large prostate, an open simple prostatectomy was previously considered the gold standard surgical treatment. However, the recently updated American Urological Association (AUA) guidelines on su...

Framework of Computer Aided Diagnosis Systems for Cancer Classification Based on Medical Images.

Early detection of cancer can increase patients' survivability and treatment options. Medical images such as Mammogram, Ultrasound, Magnetic Resonance...

Enabling Precision Medicine through Integrative Network Models.

A key challenge in precision medicine lies in understanding molecular-level underpinnings of complex human disease. Biological networks in multicellul...

Assessment of Functional Phosphatidylinositol 3-Kinase Pathway Activity in Cancer Tissue Using Forkhead Box-O Target Gene Expression in a Knowledge-Based Computational Model.

The phosphatidylinositol 3-kinase (PI3K) pathway is commonly activated in cancer. Tumors are potentially sensitive to PI3K pathway inhibitors, but rel...

Lupus nephritis pathology prediction with clinical indices.

Effective treatment of lupus nephritis and assessment of patient prognosis depend on accurate pathological classification and careful use of acute and...

Study on Contribution of Biological Interpretable and Computer-Aided Features Towards the Classification of Childhood Medulloblastoma Cells.

Diagnosis and Prognosis of brain tumour in children is always a critical case. Medulloblastoma is that subtype of brain tumour which occurs most frequ...

Unsupervised Learning for Cell-Level Visual Representation in Histopathology Images With Generative Adversarial Networks.

The visual attributes of cells, such as the nuclear morphology and chromatin openness, are critical for histopathology image analysis. By learning cel...

A Novel Morphological Marker for the Analysis of Molecular Activities at the Single-cell Level.

For more than a century, hematoxylin and eosin (H&E) staining has been the de facto standard for histological studies. Consequently, the legacy of his...

Automatic identification of clinically relevant regions from oral tissue histological images for oral squamous cell carcinoma diagnosis.

Identification of various constituent layers such as epithelial, subepithelial, and keratin of oral mucosa and characterization of keratin pearls with...

Design and Evaluation of FBG-Based Tension Sensor in Laparoscope Surgical Robots.

Due to the narrow space and a harsh chemical environment in the sterilization processes for the end-effector of surgical robots, it is difficult to in...

Deep Learning Global Glomerulosclerosis in Transplant Kidney Frozen Sections.

Transplantable kidneys are in very limited supply. Accurate viability assessment prior to transplantation could minimize organ discard. Rapid and accu...

Network-based association analysis to infer new disease-gene relationships using large-scale protein interactions.

Protein-protein interactions integrated with disease-gene associations represent important information for revealing protein functions under disease c...

Identification of cervical cancer using laser-induced breakdown spectroscopy coupled with principal component analysis and support vector machine.

Cervical cancer is one of the most widespread diseases in women. Traditional cancer diagnosis is extremely complicated and relies on subjective interp...

Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound.

Temporal enhanced ultrasound (TeUS), comprising the analysis of variations in backscattered signals from a tissue over a sequence of ultrasound frames...

Biological classification with RNA-seq data: Can alternatively spliced transcript expression enhance machine learning classifiers?

RNA sequencing (RNA-seq) is becoming a prevalent approach to quantify gene expression and is expected to gain better insights into a number of biologi...

Identification of differentially expressed genes associated with asthma in children based on the bioanalysis of the regulatory network.

Asthma, the most common chronic respiratory tract disease in children, is characterized by allergy, recurring airway obstruction and bronchospasm. The...

Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination.

This research aims to address the problem of discriminating benign cysts from malignant masses in breast ultrasound (BUS) images based on Convolutiona...

Advances in the computational and molecular understanding of the prostate cancer cell nucleus.

Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that ...

A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification.

A computer-aided diagnosis (CAD) system requires detection, segmentation, and classification in one framework to assist radiologists efficiently in an...