BACKGROUND： It is not possible to reconstruct the inner structure of the spinal cord, such as gray matter and spinal tracts, from the Visual Human Project database or CT and MRI databases, due to low image resolution...BACKGROUND： It is not possible to reconstruct the inner structure of the spinal cord, such as gray matter and spinal tracts, from the Visual Human Project database or CT and MRI databases, due to low image resolution and contrast in macrosection images. OBJECTIVE： To explore a semi-automatic computerized three-dimensional （3D） reconstruction of human spinal cord based on histological serial sections, in order to solve issues such as low contrast. DESIGN, TIME AND SETTING： An experimental study combining serial section techniques and 3D reconstruction, performed in the laboratory of Human Anatomy and Histoembryology at the Medical School of Nantong University during January to April 2008. SETTING： Department of Anatomy, Institute of Neurobiology, Jiangsu Province Key Laboratory of Neural Regeneration, Laboratory of Image Engineering. MATERIALS： A human lumbar spinal cord segment from fresh autopsy material of an adult male. METHODS： After 4% paraformaldehyde fixation for three days, serial sections of the lumbar spinal cord were cut on a Leica cryostat and mounted on slides in sequence, with eight sections aligned separately on each slide. All sections were stained with Luxol Fast Blue to reveal myelin sheaths. After gradient dehydration and clearing, the stained slides were coverslipped. Sections were observed and images recorded under a light microscope using a digital camera. Six images were acquired at x25 magnification and automatically stitched into a complete section image. After all serial images were obtained, 96 complete serial images of the human lumbar cord segment were automatically processed with ＂Curves＂, ＂Autocontrast＂, ＂Gray scale 8 bit＂, ＂Invert＂, ＂Image resize to 50%＂ steps using Photoshop 7.0 software. All images were added in order into 3D-DOCTOR 4.0 software as a stack, where serial images were automatically realigned with neighboring images and semi-automatically segmented for white matter and gray matter. Finally, simple surface and volume reconstruction were completed on a personal computer. The reconstructed human lumbar spinal cord segment was interactively observed, cut, and measured. MAIN OUTCOME MEASURES： The reconstructed human lumbar spinal cord segment. RESULTS： Compared with serial images obtained from other image modalities, such as CT, MRI, and macrosections from The Visual Human Project database, the Luxol Fast Blue stained histological serial section images exhibited higher resolution and contrast between gray and white matter. Image processing and 3D reconstruction steps were semi-automatically performed with related software. The 3D reconstructed human lumbar cord segment were observed, cut, and measured on a PC. CONCLUSION： A semi-automatically computerized method, based on histological serial sections, is an effective way to 3D-reconstruct the human spinal cord.展开更多
The measurement of thickness of material removed between serial sections is a crucial step of three-dimensional reconstruction. Active contour model is an efficient method for contour detection of objects on an image....The measurement of thickness of material removed between serial sections is a crucial step of three-dimensional reconstruction. Active contour model is an efficient method for contour detection of objects on an image. Based on the segmentation of the FeAl/ZrO2 composite image by using adaptive threshold, the gradient vector flow (GVF) snake was used to detect the contour of the indent. The horizontal diagonal length and the vertical diagonal length of the indent contour were acquired by measuring the distance from the uppermost snaxel to the lowermost snaxel and that from the leftmost snaxel to the rightmost snaxel respectively. Then the final diagonal length was gotten by averaging the vertical diagonal length and the horizontal diagonal length. The Vickers indenter was made by a square pyramidal-shaped diamond with opposite faces at an angle of 136°, so the geometrical relation was established between the thickness of material removed between two successive serial sections and the difference of diagonal length on the two serial sections. Based on the relation, the thickness of material removed between two successive serial sections was calculated using the two successive diagonals.展开更多
The key of tissue section technique is the selection and application of the embedding agent. Based on the specific characteristics of the tissue and outer skeleton of insects, a new kind of embedding agent, colophony ...The key of tissue section technique is the selection and application of the embedding agent. Based on the specific characteristics of the tissue and outer skeleton of insects, a new kind of embedding agent, colophony and paraffin (CP), was used without destroying the integrity of insect organs. The tissue can be sliced continuously by the use of CP embedding technique. It solves the 3 difficult problems in the serial section of the organ and tissue of insect, namely stiff materials, thin section and continuity of sections. These difficult problems are not solved by any unitary tissue section technique that is used now, including the paraffin section technique. By using the CP embedding technique, any parts or organs (like antenna, leg and wing) and even the whole body of insects (mini body) can be sliced up continuously. It will open up wide possibilities for the study of inner structure, the interrelations among organs, the micro-characteristics and the physiological functions of insects展开更多
A new method for reconstructing a 3-dimensional object from serial cross-sectionsis presented in this paper.The method is based on the principle of sampling and considersevery point in cross-sections as a sampling poi...A new method for reconstructing a 3-dimensional object from serial cross-sectionsis presented in this paper.The method is based on the principle of sampling and considersevery point in cross-sections as a sampling point and performs the interpolating of nonlinearfunction with these sampling points.Compared with other methods,this method has manyadvantages such as higher precision and fewer requested known sampling points.The result ofreconstruction with this method is an“entity”which involves the exterior shape and interiorconstruction information of the object simultaneously.展开更多
Fractures are critical to subsurface activities such as oil and gas extraction,geothermal energy production,and carbon storage.Hydraulic fracturing,a technique that enhances fluid production,creates complex fracture n...Fractures are critical to subsurface activities such as oil and gas extraction,geothermal energy production,and carbon storage.Hydraulic fracturing,a technique that enhances fluid production,creates complex fracture networks within rock formations containing natural discontinuities.Accurately distinguishing between hydraulically induced fractures and pre-existing discontinuities is essential for understanding hydraulic fracture mechanisms.However,this remains challenging due to the interconnected nature of fractures in three-dimensional(3D)space.Manual segmentation,while adaptive,is both labor-intensive and subjective,making it impractical for large-scale 3D datasets.This study introduces a deep learning-based progressive cross-sectional segmentation method to automate the classification of 3D fracture volumes.The proposed method was applied to a 3D hydraulic fracture network in a Montney cube sample,successfully segmenting natural fractures,parted bedding planes,and hydraulic fractures with minimal user intervention.The automated approach achieves a 99.6%reduction in manual image processing workload while maintaining high segmentation accuracy,with test accuracy exceeding 98%and F1-score over 84%.This approach generalizes well to Brazilian disc samples with different fracture patterns,achieving consistently high accuracy in distinguishing between bedding and non-bedding fractures.This automated fracture segmentation method offers an effective tool for enhanced quantitative characterization of fracture networks,which would contribute to a deeper understanding of hydraulic fracturing processes.展开更多
Understanding the structure and working principle of brain neural networks requires three-dimensional reconstruction of brain tissue samples using array tomography method.In order to improve the reconstruction perform...Understanding the structure and working principle of brain neural networks requires three-dimensional reconstruction of brain tissue samples using array tomography method.In order to improve the reconstruction performance,the sequence of brain sections should be collected with silicon wafers for subsequent electron microscopic imaging.However,the current collection of brain sections based on silicon substrate involve mainly manual collection,which requires the involvement of automation techniques to increase collection efficiency.This paper presents the design of an automatic collection device for brain sections.First,a novel mechanism based on circular silicon substrates is proposed for collection of brain sections;second,an automatic collection system based on microscopic object detection and feedback control strategy is proposed.Experimental results verify the function of the proposed collection device.Three objects(brain section,left baffle,right baffle)can be detected from microscopic images by the proposed detection method.Collection efficiency can be further improved with position feedback of brain sections well.It has been experimentally verified that the proposed device can well fulfill the task of automatic collection of brain sections.With the help of the proposed automatic collection device,human operators can be partially liberated from the tedious manual collection process and collection efficiency can be improved.展开更多
基金Natural Science Research Plan forJiangsu Colleges, No.05KJB180105 Postgraduate Innovation Cultivating Projectin Jiangsu Province, No.CX07s_035z
文摘BACKGROUND： It is not possible to reconstruct the inner structure of the spinal cord, such as gray matter and spinal tracts, from the Visual Human Project database or CT and MRI databases, due to low image resolution and contrast in macrosection images. OBJECTIVE： To explore a semi-automatic computerized three-dimensional （3D） reconstruction of human spinal cord based on histological serial sections, in order to solve issues such as low contrast. DESIGN, TIME AND SETTING： An experimental study combining serial section techniques and 3D reconstruction, performed in the laboratory of Human Anatomy and Histoembryology at the Medical School of Nantong University during January to April 2008. SETTING： Department of Anatomy, Institute of Neurobiology, Jiangsu Province Key Laboratory of Neural Regeneration, Laboratory of Image Engineering. MATERIALS： A human lumbar spinal cord segment from fresh autopsy material of an adult male. METHODS： After 4% paraformaldehyde fixation for three days, serial sections of the lumbar spinal cord were cut on a Leica cryostat and mounted on slides in sequence, with eight sections aligned separately on each slide. All sections were stained with Luxol Fast Blue to reveal myelin sheaths. After gradient dehydration and clearing, the stained slides were coverslipped. Sections were observed and images recorded under a light microscope using a digital camera. Six images were acquired at x25 magnification and automatically stitched into a complete section image. After all serial images were obtained, 96 complete serial images of the human lumbar cord segment were automatically processed with ＂Curves＂, ＂Autocontrast＂, ＂Gray scale 8 bit＂, ＂Invert＂, ＂Image resize to 50%＂ steps using Photoshop 7.0 software. All images were added in order into 3D-DOCTOR 4.0 software as a stack, where serial images were automatically realigned with neighboring images and semi-automatically segmented for white matter and gray matter. Finally, simple surface and volume reconstruction were completed on a personal computer. The reconstructed human lumbar spinal cord segment was interactively observed, cut, and measured. MAIN OUTCOME MEASURES： The reconstructed human lumbar spinal cord segment. RESULTS： Compared with serial images obtained from other image modalities, such as CT, MRI, and macrosections from The Visual Human Project database, the Luxol Fast Blue stained histological serial section images exhibited higher resolution and contrast between gray and white matter. Image processing and 3D reconstruction steps were semi-automatically performed with related software. The 3D reconstructed human lumbar cord segment were observed, cut, and measured on a PC. CONCLUSION： A semi-automatically computerized method, based on histological serial sections, is an effective way to 3D-reconstruct the human spinal cord.
基金Sponsored by the National Natural Science Foundation of China (Grant No.60873089)the Doctoral Fund of Shandong Province( Grant No.2007BS04018)
文摘The measurement of thickness of material removed between serial sections is a crucial step of three-dimensional reconstruction. Active contour model is an efficient method for contour detection of objects on an image. Based on the segmentation of the FeAl/ZrO2 composite image by using adaptive threshold, the gradient vector flow (GVF) snake was used to detect the contour of the indent. The horizontal diagonal length and the vertical diagonal length of the indent contour were acquired by measuring the distance from the uppermost snaxel to the lowermost snaxel and that from the leftmost snaxel to the rightmost snaxel respectively. Then the final diagonal length was gotten by averaging the vertical diagonal length and the horizontal diagonal length. The Vickers indenter was made by a square pyramidal-shaped diamond with opposite faces at an angle of 136°, so the geometrical relation was established between the thickness of material removed between two successive serial sections and the difference of diagonal length on the two serial sections. Based on the relation, the thickness of material removed between two successive serial sections was calculated using the two successive diagonals.
文摘The key of tissue section technique is the selection and application of the embedding agent. Based on the specific characteristics of the tissue and outer skeleton of insects, a new kind of embedding agent, colophony and paraffin (CP), was used without destroying the integrity of insect organs. The tissue can be sliced continuously by the use of CP embedding technique. It solves the 3 difficult problems in the serial section of the organ and tissue of insect, namely stiff materials, thin section and continuity of sections. These difficult problems are not solved by any unitary tissue section technique that is used now, including the paraffin section technique. By using the CP embedding technique, any parts or organs (like antenna, leg and wing) and even the whole body of insects (mini body) can be sliced up continuously. It will open up wide possibilities for the study of inner structure, the interrelations among organs, the micro-characteristics and the physiological functions of insects
文摘A new method for reconstructing a 3-dimensional object from serial cross-sectionsis presented in this paper.The method is based on the principle of sampling and considersevery point in cross-sections as a sampling point and performs the interpolating of nonlinearfunction with these sampling points.Compared with other methods,this method has manyadvantages such as higher precision and fewer requested known sampling points.The result ofreconstruction with this method is an“entity”which involves the exterior shape and interiorconstruction information of the object simultaneously.
基金supported through the Natural Sciences and Engineering Research Council of Canada(NSERC)Discovery Grants 341275,CRDPJ 543894-19NSERC/Energi Simulation Industrial Research Chair program.
文摘Fractures are critical to subsurface activities such as oil and gas extraction,geothermal energy production,and carbon storage.Hydraulic fracturing,a technique that enhances fluid production,creates complex fracture networks within rock formations containing natural discontinuities.Accurately distinguishing between hydraulically induced fractures and pre-existing discontinuities is essential for understanding hydraulic fracture mechanisms.However,this remains challenging due to the interconnected nature of fractures in three-dimensional(3D)space.Manual segmentation,while adaptive,is both labor-intensive and subjective,making it impractical for large-scale 3D datasets.This study introduces a deep learning-based progressive cross-sectional segmentation method to automate the classification of 3D fracture volumes.The proposed method was applied to a 3D hydraulic fracture network in a Montney cube sample,successfully segmenting natural fractures,parted bedding planes,and hydraulic fractures with minimal user intervention.The automated approach achieves a 99.6%reduction in manual image processing workload while maintaining high segmentation accuracy,with test accuracy exceeding 98%and F1-score over 84%.This approach generalizes well to Brazilian disc samples with different fracture patterns,achieving consistently high accuracy in distinguishing between bedding and non-bedding fractures.This automated fracture segmentation method offers an effective tool for enhanced quantitative characterization of fracture networks,which would contribute to a deeper understanding of hydraulic fracturing processes.
基金supported in part by the National Natural Science Foundation of China(61873268,62025307,U1913209)the Beijing Natural Science Foundation(JQ19020)。
文摘Understanding the structure and working principle of brain neural networks requires three-dimensional reconstruction of brain tissue samples using array tomography method.In order to improve the reconstruction performance,the sequence of brain sections should be collected with silicon wafers for subsequent electron microscopic imaging.However,the current collection of brain sections based on silicon substrate involve mainly manual collection,which requires the involvement of automation techniques to increase collection efficiency.This paper presents the design of an automatic collection device for brain sections.First,a novel mechanism based on circular silicon substrates is proposed for collection of brain sections;second,an automatic collection system based on microscopic object detection and feedback control strategy is proposed.Experimental results verify the function of the proposed collection device.Three objects(brain section,left baffle,right baffle)can be detected from microscopic images by the proposed detection method.Collection efficiency can be further improved with position feedback of brain sections well.It has been experimentally verified that the proposed device can well fulfill the task of automatic collection of brain sections.With the help of the proposed automatic collection device,human operators can be partially liberated from the tedious manual collection process and collection efficiency can be improved.
