Lalit Mohan Aggarwal

Automated medical image segmentation techniques.

Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

Segmentation and classification of medical images using texture-primitive features: Application of BAM-type artificial neural network

The objective of developing this software is to achieve auto-segmentation and tissue characterization. Therefore, the present algorithm has been designed and developed for analysis of medical images based on hybridization of syntactic and statistical approaches, using artificial neural network (ANN). This algorithm performs segmentation and classification as is done in human vision system, which recognizes objects; perceives depth; identifies different textures, curved surfaces, or a surface inclination by texture information and brightness. The analysis of medical image is directly based on four steps: 1) image filtering, 2) segmentation, 3) feature extraction, and 4) analysis of extracted features by pattern recognition system or classifier. In this paper, an attempt has been made to present an approach for soft tissue characterization utilizing texture-primitive features with ANN as segmentation and classifier tool. The present approach directly combines second, third, and fourth steps into one algorithm. This is a semisupervised approach in which supervision is involved only at the level of defining texture-primitive cell; afterwards, algorithm itself scans the whole image and performs the segmentation and classification in unsupervised mode. The algorithm was first tested on Markov textures, and the success rate achieved in classification was 100%; further, the algorithm was able to give results on the test images impregnated with distorted Markov texture cell. In addition to this, the output also indicated the level of distortion in distorted Markov texture cell as compared to standard Markov texture cell. Finally, algorithm was applied to selected medical images for segmentation and classification. Results were in agreement with those with manual segmentation and were clinically correlated.

Segmentation of medical images using Simulated Annealing Based Fuzzy C Means algorithm

Accurate segmentation is desirable for analysis and diagnosis of medical images. This study provides methodology for fully automated simulated annealing based fuzzy c-means algorithm, modelled as graph search method. The approach is unsupervised based on pixel clustering using textural features. The virtually training free algorithm needs initial temperature and cooling rate as input parameters. Experimentation on more than 180 MR and CT images for different parameter values, has suggested the best-suited values for accurate segmentation. An overall 97% correct segmentation has been achieved. The results, evaluated by radiologists, are of clinical importance for segmentation and classification of Region of Interest.

A study to improve the image quality in low-dose computed tomography (SPECT) using filtration

Background: The output of the X-ray tube used in computed tomography (CT) provides a spectrum of photon energies. Low-energy photons are preferentially absorbed in tissue; the beam spectrum shifts toward the higher energy end as it passes through more tissue, thereby changing its effective attenuation coefficient and producing a variety of artifacts (beam-hardening effects) in images. Filtering of the beam may be used to remove low-energy photon component. The accuracy of attenuation coefficient calculation by bilinear model depends highly upon accuracy of Hounsfield units. Therefore, we have made an attempt to minimize the beam-hardening effects using additional copper filter in the X-ray beam. The quantitative evaluation were made to see the effect of additional filters on resulting CT images. Materials and Methods: This study was performed on dual-head SPECT (HAWKEYE 4, GE Healthcare) with low-dose CT which acquires images at peak voltages of 120/140 kV and a tube current of 2.5 mA. For the evaluation of image quality, we used CT QA Phantom (PHILIPS) having six different density pins of Water, Polyethylene, Nylon (Aculon), Lexan, Acrylic (Perspex) and Teflon. The axial images were acquired using copper filters of various thicknesses ranging from 1 to 5 mm in steps of 1 mm. The copper filter was designed in such a manner that it fits exactly on the collimator cover of CT X-ray tube. Appropriate fixation of the copper filter was ensured before starting the image acquisition. As our intention was only to see the effect of beam hardening on the attenuation map, no SPECT study was performed. First set of images was acquired without putting any filter into the beam. Then, successively, filters of different thicknesses were placed into the beam and calibration of the CT scanner was performed before acquiring the images. The X-ray tube parameters were kept the same as that of unfiltered X-ray beam. All the acquired image sets were displayed using Xeleris 2 (GE Healthcare) on a high-resolution monitor. Moreover, Jaszaks SPECT Phantom after removing the spheres was used to see the different contrast intensities by inserting the different contrast materials of iodine and bismuth in water as background media. Images were analyzed for visibility, spatial resolution and contrast. Results: Successive improvement in the image quality was noticed when we increased the filter thickness from 1 to 3 mm. The images acquired with 3-mm filter appeared almost with no artifacts and were visibly sharper. Lower energy photons from X-ray beam cause a number of artifacts, especially at bone–tissue interfaces. Additional filtrations removed lower energy photons and improved the image quality. Degradation in the image quality was noticed when we increased the filter thickness further to 4 and 5 mm. This degradation in image quality happened due to reduced photon flux of the resulting X-ray beam, causing high statistical noise. The spatial resolution for image matrix of 512 × 512 was found to be 1.29, 1.07, 0.64 and 0.54 mm for without filter, with 1, 2 and 3 mm filters, respectively. The image quality was further analyzed for signal-to-noise ratio (SNR). It was found to be 1.72, 1.78, 1.98 and 1.99 for open, with 1, 2 and 3 mm filters respectively. This shows that 3-mm filter results in an improvement of 15.7% in SNR. Conclusion: On the basis of this study, we could conclude that use of 3-mm copper filter in the X-ray beam is optimal for removing the artifacts without causing any significant reduction in the photon flux of the resulting X-ray beam. We also propose that as artifacts have been removed from the images, the value of Hounsfield units will be more accurate and hence the value of attenuation coefficients lead to better contrast and visualization of SPECT images.

Development of an electronic radiation oncology patient information management system

The quality of patient care is critically influenced by the availability of accurate information and its efficient management. Radiation oncology consists of many information components, for example there may be information related to the patient (e.g., profile, disease site, stage, etc.), to people (radiation oncologists, radiological physicists, technologists, etc.), and to equipment (diagnostic, planning, treatment, etc.). These different data must be integrated. A comprehensive information management system is essential for efficient storage and retrieval of the enormous amounts of information. A radiation therapy patient information system (RTPIS) has been developed using open source software. PHP and JAVA script was used as the programming languages, MySQL as the database, and HTML and CSF as the design tool. This system utilizes typical web browsing technology using a WAMP5 server. Any user having a unique user ID and password can access this RTPIS. The user ID and password is issued separately to each individual according to the persons job responsibilities and accountability, so that users will be able to only access data that is related to their job responsibilities. With this system authentic users will be able to use a simple web browsing procedure to gain instant access. All types of users in the radiation oncology department should find it user-friendly. The maintenance of the system will not require large human resources or space. The file storage and retrieval process would be be satisfactory, unique, uniform, and easily accessible with adequate data protection. There will be very little possibility of unauthorized handling with this system. There will also be minimal risk of loss or accidental destruction of information.

Evaluation of single-photon emission computed tomography images obtained with and without copper filter by segmentation.

Background: Measurement of accurate attenuation of photon flux in tissue is important to obtain reconstructed images using single-photon emission computed tomography (SPECT). Computed tomography (CT) scanner provides attenuation correction data for SPECT as well as anatomic information for diagnostic purposes. Segmentation is a process of dividing an image into regions having similar properties such as gray level, color, texture, brightness, and contrast. Image segmentation is an important tool for evaluation of medical images. X-ray beam used in CT scan is poly-energetic; therefore, we have used a copper filter to remove the low energy X-rays for obtaining correct attenuation factor. Images obtained with and without filters were quantitatively evaluated by segmentation method to avoid human error. Materials and Methods: Axial images of AAPM CT phantom were acquired with 3 mm copper filter (low intensity) and without copper filter (high intensity) using low-dose CT (140 kvp and 2.5 mA) of SPECT/CT system (Hawkeye, GE Healthcare). For segmentation Simulated Annealing Based Fuzzy c-means, algorithm is applied. Quantitative measurement of quality is done based on universal image quality index. Further, for the validation of attenuation correction map of filtered CT images, Jaszczak SPECT phantom was filled with 500 MBq of 99m Tc and SPECT study was acquired. Low dose CT images were acquired for attenuation correction to be used for reconstruction of SPECT images. Another set of CT images were acquired after applying additional 3 mm copper filter. Two sets of axial SPECT images were reconstructed using attenuation map from both the CT images obtained without and with a filter. Results and Conclusions: When we applied Simulated Annealing Based Fuzzy c-means segmentation on both the CT images, the CT images with filter shows remarkable improvement and all the six section of the spheres in the Jaszczak SPECT phantom were clearly visualized.

Polylactide-co-glycolide nanoparticles of antitubercular drugs: formulation, characterization and biodistribution studies

BACKGROUND The present study was designed to prepare and characterize poly lactide-co-glycolide nanoparticles of antitubercular drugs (ATDs) for delivery through oral route to alveolar macrophages. METHODS Nanoparticles were prepared by double emulsification solvent evaporation method. Ex vivo and in vivo drug accumulation studies were performed in alveolar macrophages, harvested by broncheoalveolar lavaging. Internalization of nanoparticles was studied by confocal laser scanning microscopy. γ-scintigraphy imaging using technetium-99m was done to study the biodistribution pattern of nanoparticles. RESULTS High intracellular concentrations of ATDs were observed in macrophages within 30 min of administration of nanoparticles. Intense radioactivity recorded in liver, spleen and lungs revealed uptake of nanoparticles in macrophages, abundantly present in mononuclear phagocyte system present in these organs. CONCLUSION Targeted delivery of ATDs will help reduce dose and associated side effects including hepatotoxicity of ATDs. Further studies are required to assess the potential therapeutic advantages for treatment of TB.

Experience of wireless local area network in a radiation oncology department

The aim of this work is to develop a wireless local area network (LAN) between different types of users (Radiation Oncologists, Radiological Physicists, Radiation Technologists, etc) for efficient patient data management and to made easy the availability of information (chair side) to improve the quality of patient care in Radiation Oncology department. We have used mobile workstations (Laptops) and stationary workstations, all equipped with wireless-fidelity (Wi-Fi) access. Wireless standard 802.11g (as recommended by Institute of Electrical and Electronic Engineers (IEEE, Piscataway, NJ) has been used. The wireless networking was configured with the Service Set Identifier (SSID), Media Access Control (MAC) address filtering, and Wired Equivalent Privacy (WEP) network securities. We are successfully using this wireless network in sharing the indigenously developed patient information management software. The proper selection of the hardware and the software combined with a secure wireless LAN setup will lead to a more efficient and productive radiation oncology department.

A new method to correct the attenuation map in simultaneous transmission/emission tomography using 153Gd/ 67Ga radioisotopes

Reconstruction of the tomographic images without attenuation correction can cause erroneously high count densities and reduced image contrast in low attenuation regions. In order to solve the problem of photon attenuation, one needs to know the attenuation coefficient for the individual patient being studied. Therefore, we made an attempt to correct the attenuation map in simultaneous transmission/emission tomography with 153Gd/67Ga using maximum likelihood method using the expectation maximization (ML-EM) algorithm to correct the transmission window for both the spillover and downscatter. Spillover fraction, scatter fraction and parameters for the scatter function (A, b and c) were determined experimentally and optimized using the optimization program written in IDL based on simplex theory. All measurements were performed on a Vertex gamma camera using the anthropomorphic thorax phantom for validation of data obtained by the proposed method. It was observed that without spillover and downscatter correction, the mean counts were 19.29 in liver and 26.90 in lung, whereas after after applying the corrections, the mean counts were reduced to 3.80 and 15.10 in liver and lung, respectively, which were close to true mean counts (liver 2.15 and lung 14.89). In this proposed method, we introduced the set of Ft(spillover) and Kt(downscatter) to account for the variations in projection pixels (ft and kt) with the density and thickness. The Ft and Kt were determined using the transmission data by an iterative process. The quantitative error was reduced by 98.0% for lung and 90.0% for liver when the corrected transmission images were obtained after the subtraction of spillover and downscatter fraction.

Design and development of novel p-aminobenzoic acid derivatives as potential cholinesterase inhibitors for the treatment of Alzheimer’s disease

Based on the quantitative structure-activity relationship (QSAR), some novel p-aminobenzoic acid derivatives as promising cholinesterase enzyme inhibitors were designed, synthesized, characterized and evaluated to enhance learning and memory. The in vitro enzyme kinetic study of the synthesized compounds revealed the type of inhibition on the respective acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. The in vivo studies of the synthesized compounds exhibited significant reversal of cognitive deficits in the animal models of amnesia as compared to standard drug donepezil. Further, the ex vivo studies in the specific brain regions like the hippocampus, hypothalamus, and prefrontal cortex regions also exhibited AChE inhibition comparable to standard donepezil. The in silico molecular docking and dynamics simulations studies of the most potent compound 22 revealed the consensual interactions at the active site pocket of the AChE.