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Related Concept Videos

Classification of Skeletal Muscle Fibers01:48

Classification of Skeletal Muscle Fibers

Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
Slow-Twitch Muscle Fibers
Slow oxidative, muscle fibers appear red due to large numbers of capillaries and high levels of...
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Muscles that Move the Leg

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Anterior Compartment
The quadriceps femoris, the most visible muscle of the anterior compartment, is integral for leg extension and thigh flexion. It is formed by merging four distinct muscles — the vastus lateralis, vastus medialis, vastus intermedius, and rectus femoris. The quadriceps tendon, a shared tendon of the four quadriceps muscles, is affixed to...
Functional Classification of Joints01:09

Functional Classification of Joints

Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An immobile...

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Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics
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Probabilistic multi-shape segmentation of knee extensor and flexor muscles.

Shawn Andrews1, Ghassan Hamarneh, Azadeh Yazdanpanah

  • 1Medical Image Analysis Lab, Simon Fraser University, Canada. sda56@sfu.ca

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 19, 2011
PubMed
Summary

A new automatic method accurately segments lower limb muscles in patients with chronic obstructive pulmonary disease (COPD). This advance aids in analyzing muscle shape and size for improved COPD therapy and patient outcomes.

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Area of Science:

  • Medical imaging analysis
  • Biomedical engineering
  • Radiology

Background:

  • Chronic obstructive pulmonary disease (COPD) is frequently associated with lower limb skeletal muscle weakness.
  • Accurate analysis of muscle morphology is crucial for developing effective therapeutic strategies for COPD patients.
  • Segmentation of individual lower limb muscles is challenging due to image data limitations.

Purpose of the Study:

  • To develop a fully automatic method for segmenting lower limb skeletal muscles in COPD patients.
  • To overcome challenges related to image information scarcity in muscle segmentation.
  • To provide accurate muscle segmentation for morphological analysis.

Main Methods:

  • Implementation of a fully automatic segmentation technique for lower limb muscles.
  • Enforcement of a multi-region shape prior to ensure segmentation feasibility.
  • Utilizing an energy-minimizing probabilistic approach to identify segmentation uncertainties.

Main Results:

  • The developed method achieved accurate segmentation of different lower limb muscles.
  • Experiments on 3D MRI datasets demonstrated high performance.
  • An average Dice similarity coefficient of 0.92 +/- 0.03 was obtained compared to ground truth.

Conclusions:

  • The proposed automatic segmentation method effectively addresses the complexities of muscle segmentation in COPD patients.
  • This technique offers a reliable tool for analyzing muscle shape and size, potentially leading to enhanced therapeutic interventions.
  • The probabilistic output provides valuable information on segmentation confidence.