Presegmenter Cascaded Framework for Mammogram Mass Segmentation.

Accurate segmentation of breast masses in mammogram images is essential for early cancer diagnosis and treatment planning. Several deep learning (DL) models have been proposed for whole mammogram segmentation and mass patch/crop segmentation. However, current DL models for breast mammogram mass segmentation face several limitations, including false positives (FPs), false negatives (FNs), and challenges with the end-to-end approach.

Digital mammography dataset for breast cancer diagnosis research (DMID) with breast mass segmentation analysis.

In the last two decades, computer-aided detection and diagnosis (CAD) systems have been created to help radiologists discover and diagnose lesions observed on breast imaging tests. These systems can serve as a second opinion tool for the radiologist. However, developing algorithms for identifying and diagnosing breast lesions relies heavily on mammographic datasets.

Exploring the mechanism of action bitter melon in the treatment of breast cancer by network pharmacology.

Background: Bitter melon has been used to stop the growth of breast cancer (BRCA) cells. However, the underlying mechanism is still unclear.

Aim: To predict the therapeutic effect of bitter melon against BRCA using network pharmacology and to explore the underlying pharmacological mechanisms.

Rosai-Dorfman disease in a symptomatic elderly man.

An 81-year-old man presented with anemia, fatigue, weight loss, and recurrent urinary tract infections and was found to have diffuse large adenopathy and infiltrating renal masses. Surgical excision of a lymph node and histologic evaluation led to the diagnosis of Rosai-Dorfman disease, a rare histioproliferative condition that classically presents with enlarged cervical lymph nodes bilaterally. It also can involve additional nodal chains and/or have extranodal manifestations.

Use of Ga DOTATATE, a new molecular imaging agent, for neuroendocrine tumors.

Neuroendocrine tumors (NET), such as insulinomas and carcinoid tumors, can be challenging to diagnose since patients often present with vague symptoms. Adding to the challenge, these tumors are often occult on typical cross-sectional imaging modalities. Because of these challenges, there has been an increase in the utilization of radiopharmaceuticals that take advantage of specific receptors expressed by NET.