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Anatomical Positions

Anatomical Positions

In anatomy, several standard anatomical positions are used as references for describing the position and orientation of different body parts. These positions help provide a common frame of reference when discussing anatomical structures. The anatomical position is the standard reference point for describing the body's position and orientation. In this position:
The body is upright, facing forward, and standing erect.
The feet are parallel and flat on the floor.
The arms are hanging by the...

Anatomical Terminology

Anatomical Terminology

Knowledge of anatomy is essential to understand human biology and medicine. Anatomists and health care professionals use standard terminology to describe the human body with more precision and no ambiguity. Anatomical terms have mostly Greek and Latin-derived roots. Because these languages are rarely used in conversation, the meaning of words remains the same. Each term is made up of a root in between the prefixes and suffixes. The root of a term often refers to an organ, tissue, or condition,...

Anatomical Movements

Anatomical Movements

Anatomical movements refer to the various actions or motions that can be performed by the body's joints and muscles. These movements are described using specific terms to provide a standardized way of discussing and understanding the range of motion at different joints.
Here are some common anatomical movements:
Flexion and extension motions are in the sagittal (anterior–posterior) plane of motion. These movements take place at the shoulder, hip, elbow, knee, wrist,...

Cerebrum: Anatomical Overview II

Cerebrum: Anatomical Overview II

Each cerebral hemisphere can be divided into three main regions. The outermost region, the cerebral cortex, is a thin layer (2 to 4 millimeters thick) made up of gray matter, consisting of neuron cell bodies, dendrites, glial cells, and blood vessels. The middle region, or white matter, is primarily composed of myelinated nerve fibers organized into three types of large tracts: association fibers, commissures, and projection fibers. Association fibers connect different areas within the same...

Diencephalon: Anatomical Regions

Diencephalon: Anatomical Regions

The diencephalon, etymologically translated as 'through brain,' plays an integral role as the conduit between the cerebrum and the vast extent of the nervous system. However, the olfactory system is an exception, as it interfaces directly with the cerebrum. The diencephalon, deeply ensconced beneath the cerebrum, primarily consists of three paired structures — the thalamus, hypothalamus, and epithelamus. It also includes accessory structures such as the subthalamus, which houses the...

Cerebellum: Anatomical Regions

Cerebellum: Anatomical Regions

The cerebellum, also known as the "little brain," is located in the posterior cranial fossa, inferior to the tentorium cerebelli and dorsal to the brainstem. It plays a significant role in motor control, coordination, and proprioception.
Cerebellar Structure
Externally, the cerebellum features a highly convoluted surface with numerous folia (narrow ridges) separated by shallow sulci (grooves). The cerebellum is divided into two hemispheres by a thin median structure known as the vermis. The...

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Related Experiment Video

Updated: Feb 3, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Deep Learning-Based Segmentation of Cryo-Electron Tomograms

Published on: November 11, 2022

Deep Geodesic Learning for Segmentation and Anatomical Landmarking.

Neslisah Torosdagli, Denise K Liberton, Payal Verma

IEEE Transactions on Medical Imaging

|October 19, 2018

Summary

This summary is machine-generated.

This study introduces a deep learning framework for segmenting mandibles and identifying anatomical landmarks in cone-beam computed tomography (CBCT) scans, improving accuracy for craniofacial anomalies.

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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

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Published on: November 30, 2022

Area of Science:

Medical Imaging
Artificial Intelligence
Anatomy

Background:

Accurate mandible segmentation and landmark identification are crucial for diagnosing and treating craniofacial anomalies.
Current methods often require manual intervention and struggle with complex anatomical variations.

Purpose of the Study:

To develop a novel, fully automated deep learning framework for mandible segmentation and anatomical landmark localization.
To address the challenges of high variability in craniofacial anatomy and closely-spaced landmarks.

Main Methods:

A deep neural network architecture was designed for robust mandible segmentation without data augmentation.
Landmark localization was performed on the geodesic space, utilizing a long short-term memory network for precise identification of both sparse and dense landmarks.

Main Results:

The proposed automated method demonstrated superior performance compared to state-of-the-art techniques for mandible segmentation and landmarking.
The framework achieved high accuracy on a challenging dataset of CBCT scans with significant craniomaxillofacial variability.

Conclusions:

The novel deep learning framework offers a highly effective and automated solution for mandible segmentation and landmarking.
This approach shows significant potential for improving diagnostic and treatment planning in craniofacial medicine.